jeqcho commited on
Commit
a10c9ec
·
verified ·
1 Parent(s): f8f1e8d

Upload folder using huggingface_hub

Browse files
checkpoint-300/README.md ADDED
@@ -0,0 +1,210 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: unsloth/Qwen2.5-3B-Instruct
3
+ library_name: peft
4
+ pipeline_tag: text-generation
5
+ tags:
6
+ - base_model:adapter:unsloth/Qwen2.5-3B-Instruct
7
+ - lora
8
+ - sft
9
+ - transformers
10
+ - trl
11
+ - unsloth
12
+ ---
13
+
14
+ # Model Card for Model ID
15
+
16
+ <!-- Provide a quick summary of what the model is/does. -->
17
+
18
+
19
+
20
+ ## Model Details
21
+
22
+ ### Model Description
23
+
24
+ <!-- Provide a longer summary of what this model is. -->
25
+
26
+
27
+
28
+ - **Developed by:** [More Information Needed]
29
+ - **Funded by [optional]:** [More Information Needed]
30
+ - **Shared by [optional]:** [More Information Needed]
31
+ - **Model type:** [More Information Needed]
32
+ - **Language(s) (NLP):** [More Information Needed]
33
+ - **License:** [More Information Needed]
34
+ - **Finetuned from model [optional]:** [More Information Needed]
35
+
36
+ ### Model Sources [optional]
37
+
38
+ <!-- Provide the basic links for the model. -->
39
+
40
+ - **Repository:** [More Information Needed]
41
+ - **Paper [optional]:** [More Information Needed]
42
+ - **Demo [optional]:** [More Information Needed]
43
+
44
+ ## Uses
45
+
46
+ <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
47
+
48
+ ### Direct Use
49
+
50
+ <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
51
+
52
+ [More Information Needed]
53
+
54
+ ### Downstream Use [optional]
55
+
56
+ <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
57
+
58
+ [More Information Needed]
59
+
60
+ ### Out-of-Scope Use
61
+
62
+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
63
+
64
+ [More Information Needed]
65
+
66
+ ## Bias, Risks, and Limitations
67
+
68
+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
69
+
70
+ [More Information Needed]
71
+
72
+ ### Recommendations
73
+
74
+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
75
+
76
+ Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
77
+
78
+ ## How to Get Started with the Model
79
+
80
+ Use the code below to get started with the model.
81
+
82
+ [More Information Needed]
83
+
84
+ ## Training Details
85
+
86
+ ### Training Data
87
+
88
+ <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
89
+
90
+ [More Information Needed]
91
+
92
+ ### Training Procedure
93
+
94
+ <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
95
+
96
+ #### Preprocessing [optional]
97
+
98
+ [More Information Needed]
99
+
100
+
101
+ #### Training Hyperparameters
102
+
103
+ - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
104
+
105
+ #### Speeds, Sizes, Times [optional]
106
+
107
+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
108
+
109
+ [More Information Needed]
110
+
111
+ ## Evaluation
112
+
113
+ <!-- This section describes the evaluation protocols and provides the results. -->
114
+
115
+ ### Testing Data, Factors & Metrics
116
+
117
+ #### Testing Data
118
+
119
+ <!-- This should link to a Dataset Card if possible. -->
120
+
121
+ [More Information Needed]
122
+
123
+ #### Factors
124
+
125
+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
126
+
127
+ [More Information Needed]
128
+
129
+ #### Metrics
130
+
131
+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
132
+
133
+ [More Information Needed]
134
+
135
+ ### Results
136
+
137
+ [More Information Needed]
138
+
139
+ #### Summary
140
+
141
+
142
+
143
+ ## Model Examination [optional]
144
+
145
+ <!-- Relevant interpretability work for the model goes here -->
146
+
147
+ [More Information Needed]
148
+
149
+ ## Environmental Impact
150
+
151
+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
152
+
153
+ Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
154
+
155
+ - **Hardware Type:** [More Information Needed]
156
+ - **Hours used:** [More Information Needed]
157
+ - **Cloud Provider:** [More Information Needed]
158
+ - **Compute Region:** [More Information Needed]
159
+ - **Carbon Emitted:** [More Information Needed]
160
+
161
+ ## Technical Specifications [optional]
162
+
163
+ ### Model Architecture and Objective
164
+
165
+ [More Information Needed]
166
+
167
+ ### Compute Infrastructure
168
+
169
+ [More Information Needed]
170
+
171
+ #### Hardware
172
+
173
+ [More Information Needed]
174
+
175
+ #### Software
176
+
177
+ [More Information Needed]
178
+
179
+ ## Citation [optional]
180
+
181
+ <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
182
+
183
+ **BibTeX:**
184
+
185
+ [More Information Needed]
186
+
187
+ **APA:**
188
+
189
+ [More Information Needed]
190
+
191
+ ## Glossary [optional]
192
+
193
+ <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
194
+
195
+ [More Information Needed]
196
+
197
+ ## More Information [optional]
198
+
199
+ [More Information Needed]
200
+
201
+ ## Model Card Authors [optional]
202
+
203
+ [More Information Needed]
204
+
205
+ ## Model Card Contact
206
+
207
+ [More Information Needed]
208
+ ### Framework versions
209
+
210
+ - PEFT 0.19.1
checkpoint-300/adapter_config.json ADDED
@@ -0,0 +1,52 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "alora_invocation_tokens": null,
3
+ "alpha_pattern": {},
4
+ "arrow_config": null,
5
+ "auto_mapping": {
6
+ "base_model_class": "Qwen2ForCausalLM",
7
+ "parent_library": "transformers.models.qwen2.modeling_qwen2",
8
+ "unsloth_fixed": true
9
+ },
10
+ "base_model_name_or_path": "unsloth/Qwen2.5-3B-Instruct",
11
+ "bias": "none",
12
+ "corda_config": null,
13
+ "ensure_weight_tying": false,
14
+ "eva_config": null,
15
+ "exclude_modules": null,
16
+ "fan_in_fan_out": false,
17
+ "inference_mode": true,
18
+ "init_lora_weights": true,
19
+ "layer_replication": null,
20
+ "layers_pattern": null,
21
+ "layers_to_transform": null,
22
+ "loftq_config": {},
23
+ "lora_alpha": 8,
24
+ "lora_bias": false,
25
+ "lora_dropout": 0.0,
26
+ "lora_ga_config": null,
27
+ "megatron_config": null,
28
+ "megatron_core": "megatron.core",
29
+ "modules_to_save": null,
30
+ "peft_type": "LORA",
31
+ "peft_version": "0.19.1",
32
+ "qalora_group_size": 16,
33
+ "r": 8,
34
+ "rank_pattern": {},
35
+ "revision": null,
36
+ "target_modules": [
37
+ "k_proj",
38
+ "up_proj",
39
+ "gate_proj",
40
+ "o_proj",
41
+ "down_proj",
42
+ "q_proj",
43
+ "v_proj"
44
+ ],
45
+ "target_parameters": null,
46
+ "task_type": "CAUSAL_LM",
47
+ "trainable_token_indices": null,
48
+ "use_bdlora": null,
49
+ "use_dora": false,
50
+ "use_qalora": false,
51
+ "use_rslora": false
52
+ }
checkpoint-300/adapter_model.safetensors ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a55de7fd2afef8e16db3bd3d092c7c4e318f0de0c28186673cc21453985593d7
3
+ size 59933632
checkpoint-300/added_tokens.json ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "</tool_call>": 151658,
3
+ "<tool_call>": 151657,
4
+ "<|PAD_TOKEN|>": 151665,
5
+ "<|box_end|>": 151649,
6
+ "<|box_start|>": 151648,
7
+ "<|endoftext|>": 151643,
8
+ "<|file_sep|>": 151664,
9
+ "<|fim_middle|>": 151660,
10
+ "<|fim_pad|>": 151662,
11
+ "<|fim_prefix|>": 151659,
12
+ "<|fim_suffix|>": 151661,
13
+ "<|im_end|>": 151645,
14
+ "<|im_start|>": 151644,
15
+ "<|image_pad|>": 151655,
16
+ "<|object_ref_end|>": 151647,
17
+ "<|object_ref_start|>": 151646,
18
+ "<|quad_end|>": 151651,
19
+ "<|quad_start|>": 151650,
20
+ "<|repo_name|>": 151663,
21
+ "<|video_pad|>": 151656,
22
+ "<|vision_end|>": 151653,
23
+ "<|vision_pad|>": 151654,
24
+ "<|vision_start|>": 151652
25
+ }
checkpoint-300/chat_template.jinja ADDED
@@ -0,0 +1,54 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {%- if tools %}
2
+ {{- '<|im_start|>system\n' }}
3
+ {%- if messages[0]['role'] == 'system' %}
4
+ {{- messages[0]['content'] }}
5
+ {%- else %}
6
+ {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
7
+ {%- endif %}
8
+ {{- "\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
9
+ {%- for tool in tools %}
10
+ {{- "\n" }}
11
+ {{- tool | tojson }}
12
+ {%- endfor %}
13
+ {{- "\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{\"name\": <function-name>, \"arguments\": <args-json-object>}\n</tool_call><|im_end|>\n" }}
14
+ {%- else %}
15
+ {%- if messages[0]['role'] == 'system' %}
16
+ {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
17
+ {%- else %}
18
+ {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
19
+ {%- endif %}
20
+ {%- endif %}
21
+ {%- for message in messages %}
22
+ {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
23
+ {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
24
+ {%- elif message.role == "assistant" %}
25
+ {{- '<|im_start|>' + message.role }}
26
+ {%- if message.content %}
27
+ {{- '\n' + message.content }}
28
+ {%- endif %}
29
+ {%- for tool_call in message.tool_calls %}
30
+ {%- if tool_call.function is defined %}
31
+ {%- set tool_call = tool_call.function %}
32
+ {%- endif %}
33
+ {{- '\n<tool_call>\n{"name": "' }}
34
+ {{- tool_call.name }}
35
+ {{- '", "arguments": ' }}
36
+ {{- tool_call.arguments | tojson }}
37
+ {{- '}\n</tool_call>' }}
38
+ {%- endfor %}
39
+ {{- '<|im_end|>\n' }}
40
+ {%- elif message.role == "tool" %}
41
+ {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
42
+ {{- '<|im_start|>user' }}
43
+ {%- endif %}
44
+ {{- '\n<tool_response>\n' }}
45
+ {{- message.content }}
46
+ {{- '\n</tool_response>' }}
47
+ {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
48
+ {{- '<|im_end|>\n' }}
49
+ {%- endif %}
50
+ {%- endif %}
51
+ {%- endfor %}
52
+ {%- if add_generation_prompt %}
53
+ {{- '<|im_start|>assistant\n' }}
54
+ {%- endif %}
checkpoint-300/merges.txt ADDED
The diff for this file is too large to render. See raw diff
 
checkpoint-300/optimizer.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:8cf616d022968f2c34c8f6869ce051c420c9340ccfff0fbebfa2795d870c4137
3
+ size 120166091
checkpoint-300/rng_state.pth ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:5cc4c4882f171836578d88678b73a58570743f8aa1254f14e32eb2bb03bddca3
3
+ size 14645
checkpoint-300/scheduler.pt ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:b2e505675c317883b766f2962f7aad0e9e7af355475f86ff6509ee84802ba836
3
+ size 1465
checkpoint-300/special_tokens_map.json ADDED
@@ -0,0 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "additional_special_tokens": [
3
+ "<|im_start|>",
4
+ "<|im_end|>",
5
+ "<|object_ref_start|>",
6
+ "<|object_ref_end|>",
7
+ "<|box_start|>",
8
+ "<|box_end|>",
9
+ "<|quad_start|>",
10
+ "<|quad_end|>",
11
+ "<|vision_start|>",
12
+ "<|vision_end|>",
13
+ "<|vision_pad|>",
14
+ "<|image_pad|>",
15
+ "<|video_pad|>"
16
+ ],
17
+ "eos_token": {
18
+ "content": "<|im_end|>",
19
+ "lstrip": false,
20
+ "normalized": false,
21
+ "rstrip": false,
22
+ "single_word": false
23
+ },
24
+ "pad_token": "<|PAD_TOKEN|>"
25
+ }
checkpoint-300/tokenizer.json ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:fab42efe8d17406525a9154b728cf9e957629a8ed7ce997770efdd71128c6a1a
3
+ size 11422086
checkpoint-300/tokenizer_config.json ADDED
@@ -0,0 +1,216 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "add_bos_token": false,
3
+ "add_prefix_space": false,
4
+ "added_tokens_decoder": {
5
+ "151643": {
6
+ "content": "<|endoftext|>",
7
+ "lstrip": false,
8
+ "normalized": false,
9
+ "rstrip": false,
10
+ "single_word": false,
11
+ "special": true
12
+ },
13
+ "151644": {
14
+ "content": "<|im_start|>",
15
+ "lstrip": false,
16
+ "normalized": false,
17
+ "rstrip": false,
18
+ "single_word": false,
19
+ "special": true
20
+ },
21
+ "151645": {
22
+ "content": "<|im_end|>",
23
+ "lstrip": false,
24
+ "normalized": false,
25
+ "rstrip": false,
26
+ "single_word": false,
27
+ "special": true
28
+ },
29
+ "151646": {
30
+ "content": "<|object_ref_start|>",
31
+ "lstrip": false,
32
+ "normalized": false,
33
+ "rstrip": false,
34
+ "single_word": false,
35
+ "special": true
36
+ },
37
+ "151647": {
38
+ "content": "<|object_ref_end|>",
39
+ "lstrip": false,
40
+ "normalized": false,
41
+ "rstrip": false,
42
+ "single_word": false,
43
+ "special": true
44
+ },
45
+ "151648": {
46
+ "content": "<|box_start|>",
47
+ "lstrip": false,
48
+ "normalized": false,
49
+ "rstrip": false,
50
+ "single_word": false,
51
+ "special": true
52
+ },
53
+ "151649": {
54
+ "content": "<|box_end|>",
55
+ "lstrip": false,
56
+ "normalized": false,
57
+ "rstrip": false,
58
+ "single_word": false,
59
+ "special": true
60
+ },
61
+ "151650": {
62
+ "content": "<|quad_start|>",
63
+ "lstrip": false,
64
+ "normalized": false,
65
+ "rstrip": false,
66
+ "single_word": false,
67
+ "special": true
68
+ },
69
+ "151651": {
70
+ "content": "<|quad_end|>",
71
+ "lstrip": false,
72
+ "normalized": false,
73
+ "rstrip": false,
74
+ "single_word": false,
75
+ "special": true
76
+ },
77
+ "151652": {
78
+ "content": "<|vision_start|>",
79
+ "lstrip": false,
80
+ "normalized": false,
81
+ "rstrip": false,
82
+ "single_word": false,
83
+ "special": true
84
+ },
85
+ "151653": {
86
+ "content": "<|vision_end|>",
87
+ "lstrip": false,
88
+ "normalized": false,
89
+ "rstrip": false,
90
+ "single_word": false,
91
+ "special": true
92
+ },
93
+ "151654": {
94
+ "content": "<|vision_pad|>",
95
+ "lstrip": false,
96
+ "normalized": false,
97
+ "rstrip": false,
98
+ "single_word": false,
99
+ "special": true
100
+ },
101
+ "151655": {
102
+ "content": "<|image_pad|>",
103
+ "lstrip": false,
104
+ "normalized": false,
105
+ "rstrip": false,
106
+ "single_word": false,
107
+ "special": true
108
+ },
109
+ "151656": {
110
+ "content": "<|video_pad|>",
111
+ "lstrip": false,
112
+ "normalized": false,
113
+ "rstrip": false,
114
+ "single_word": false,
115
+ "special": true
116
+ },
117
+ "151657": {
118
+ "content": "<tool_call>",
119
+ "lstrip": false,
120
+ "normalized": false,
121
+ "rstrip": false,
122
+ "single_word": false,
123
+ "special": false
124
+ },
125
+ "151658": {
126
+ "content": "</tool_call>",
127
+ "lstrip": false,
128
+ "normalized": false,
129
+ "rstrip": false,
130
+ "single_word": false,
131
+ "special": false
132
+ },
133
+ "151659": {
134
+ "content": "<|fim_prefix|>",
135
+ "lstrip": false,
136
+ "normalized": false,
137
+ "rstrip": false,
138
+ "single_word": false,
139
+ "special": false
140
+ },
141
+ "151660": {
142
+ "content": "<|fim_middle|>",
143
+ "lstrip": false,
144
+ "normalized": false,
145
+ "rstrip": false,
146
+ "single_word": false,
147
+ "special": false
148
+ },
149
+ "151661": {
150
+ "content": "<|fim_suffix|>",
151
+ "lstrip": false,
152
+ "normalized": false,
153
+ "rstrip": false,
154
+ "single_word": false,
155
+ "special": false
156
+ },
157
+ "151662": {
158
+ "content": "<|fim_pad|>",
159
+ "lstrip": false,
160
+ "normalized": false,
161
+ "rstrip": false,
162
+ "single_word": false,
163
+ "special": false
164
+ },
165
+ "151663": {
166
+ "content": "<|repo_name|>",
167
+ "lstrip": false,
168
+ "normalized": false,
169
+ "rstrip": false,
170
+ "single_word": false,
171
+ "special": false
172
+ },
173
+ "151664": {
174
+ "content": "<|file_sep|>",
175
+ "lstrip": false,
176
+ "normalized": false,
177
+ "rstrip": false,
178
+ "single_word": false,
179
+ "special": false
180
+ },
181
+ "151665": {
182
+ "content": "<|PAD_TOKEN|>",
183
+ "lstrip": false,
184
+ "normalized": false,
185
+ "rstrip": false,
186
+ "single_word": false,
187
+ "special": true
188
+ }
189
+ },
190
+ "additional_special_tokens": [
191
+ "<|im_start|>",
192
+ "<|im_end|>",
193
+ "<|object_ref_start|>",
194
+ "<|object_ref_end|>",
195
+ "<|box_start|>",
196
+ "<|box_end|>",
197
+ "<|quad_start|>",
198
+ "<|quad_end|>",
199
+ "<|vision_start|>",
200
+ "<|vision_end|>",
201
+ "<|vision_pad|>",
202
+ "<|image_pad|>",
203
+ "<|video_pad|>"
204
+ ],
205
+ "bos_token": null,
206
+ "clean_up_tokenization_spaces": false,
207
+ "eos_token": "<|im_end|>",
208
+ "errors": "replace",
209
+ "extra_special_tokens": {},
210
+ "model_max_length": 32768,
211
+ "pad_token": "<|PAD_TOKEN|>",
212
+ "padding_side": "right",
213
+ "split_special_tokens": false,
214
+ "tokenizer_class": "Qwen2Tokenizer",
215
+ "unk_token": null
216
+ }
checkpoint-300/trainer_state.json ADDED
@@ -0,0 +1,2134 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "best_global_step": null,
3
+ "best_metric": null,
4
+ "best_model_checkpoint": null,
5
+ "epoch": 1.975824175824176,
6
+ "eval_steps": 500,
7
+ "global_step": 300,
8
+ "is_hyper_param_search": false,
9
+ "is_local_process_zero": true,
10
+ "is_world_process_zero": true,
11
+ "log_history": [
12
+ {
13
+ "epoch": 0.006593406593406593,
14
+ "grad_norm": 2.0722603797912598,
15
+ "learning_rate": 0.0,
16
+ "loss": 3.2131,
17
+ "step": 1
18
+ },
19
+ {
20
+ "epoch": 0.013186813186813187,
21
+ "grad_norm": 1.6677350997924805,
22
+ "learning_rate": 4e-05,
23
+ "loss": 2.5554,
24
+ "step": 2
25
+ },
26
+ {
27
+ "epoch": 0.01978021978021978,
28
+ "grad_norm": 1.6039100885391235,
29
+ "learning_rate": 8e-05,
30
+ "loss": 2.6951,
31
+ "step": 3
32
+ },
33
+ {
34
+ "epoch": 0.026373626373626374,
35
+ "grad_norm": 1.6277270317077637,
36
+ "learning_rate": 0.00012,
37
+ "loss": 2.9003,
38
+ "step": 4
39
+ },
40
+ {
41
+ "epoch": 0.03296703296703297,
42
+ "grad_norm": 2.0207111835479736,
43
+ "learning_rate": 0.00016,
44
+ "loss": 2.6989,
45
+ "step": 5
46
+ },
47
+ {
48
+ "epoch": 0.03956043956043956,
49
+ "grad_norm": 2.6012003421783447,
50
+ "learning_rate": 0.0002,
51
+ "loss": 2.2728,
52
+ "step": 6
53
+ },
54
+ {
55
+ "epoch": 0.046153846153846156,
56
+ "grad_norm": 2.338730812072754,
57
+ "learning_rate": 0.00019955654101995565,
58
+ "loss": 1.7083,
59
+ "step": 7
60
+ },
61
+ {
62
+ "epoch": 0.05274725274725275,
63
+ "grad_norm": 2.3853142261505127,
64
+ "learning_rate": 0.00019911308203991133,
65
+ "loss": 1.5367,
66
+ "step": 8
67
+ },
68
+ {
69
+ "epoch": 0.05934065934065934,
70
+ "grad_norm": 1.1683852672576904,
71
+ "learning_rate": 0.00019866962305986697,
72
+ "loss": 1.2907,
73
+ "step": 9
74
+ },
75
+ {
76
+ "epoch": 0.06593406593406594,
77
+ "grad_norm": 0.9153192639350891,
78
+ "learning_rate": 0.00019822616407982261,
79
+ "loss": 1.16,
80
+ "step": 10
81
+ },
82
+ {
83
+ "epoch": 0.07252747252747253,
84
+ "grad_norm": 1.4894245862960815,
85
+ "learning_rate": 0.00019778270509977829,
86
+ "loss": 1.5419,
87
+ "step": 11
88
+ },
89
+ {
90
+ "epoch": 0.07912087912087912,
91
+ "grad_norm": 0.8791560530662537,
92
+ "learning_rate": 0.00019733924611973393,
93
+ "loss": 1.323,
94
+ "step": 12
95
+ },
96
+ {
97
+ "epoch": 0.08571428571428572,
98
+ "grad_norm": 0.5337121486663818,
99
+ "learning_rate": 0.0001968957871396896,
100
+ "loss": 1.1458,
101
+ "step": 13
102
+ },
103
+ {
104
+ "epoch": 0.09230769230769231,
105
+ "grad_norm": 0.5149000883102417,
106
+ "learning_rate": 0.00019645232815964525,
107
+ "loss": 1.0808,
108
+ "step": 14
109
+ },
110
+ {
111
+ "epoch": 0.0989010989010989,
112
+ "grad_norm": 0.4778643846511841,
113
+ "learning_rate": 0.00019600886917960092,
114
+ "loss": 1.088,
115
+ "step": 15
116
+ },
117
+ {
118
+ "epoch": 0.1054945054945055,
119
+ "grad_norm": 0.47255033254623413,
120
+ "learning_rate": 0.00019556541019955653,
121
+ "loss": 1.0745,
122
+ "step": 16
123
+ },
124
+ {
125
+ "epoch": 0.11208791208791209,
126
+ "grad_norm": 0.43144354224205017,
127
+ "learning_rate": 0.0001951219512195122,
128
+ "loss": 1.2685,
129
+ "step": 17
130
+ },
131
+ {
132
+ "epoch": 0.11868131868131868,
133
+ "grad_norm": 0.38666868209838867,
134
+ "learning_rate": 0.00019467849223946785,
135
+ "loss": 1.0754,
136
+ "step": 18
137
+ },
138
+ {
139
+ "epoch": 0.12527472527472527,
140
+ "grad_norm": 0.38462671637535095,
141
+ "learning_rate": 0.00019423503325942352,
142
+ "loss": 0.9311,
143
+ "step": 19
144
+ },
145
+ {
146
+ "epoch": 0.13186813186813187,
147
+ "grad_norm": 0.35871055722236633,
148
+ "learning_rate": 0.00019379157427937917,
149
+ "loss": 0.95,
150
+ "step": 20
151
+ },
152
+ {
153
+ "epoch": 0.13846153846153847,
154
+ "grad_norm": 0.43639278411865234,
155
+ "learning_rate": 0.00019334811529933484,
156
+ "loss": 0.9915,
157
+ "step": 21
158
+ },
159
+ {
160
+ "epoch": 0.14505494505494507,
161
+ "grad_norm": 0.3904358446598053,
162
+ "learning_rate": 0.00019290465631929045,
163
+ "loss": 1.0229,
164
+ "step": 22
165
+ },
166
+ {
167
+ "epoch": 0.15164835164835164,
168
+ "grad_norm": 0.3931411802768707,
169
+ "learning_rate": 0.00019246119733924613,
170
+ "loss": 0.897,
171
+ "step": 23
172
+ },
173
+ {
174
+ "epoch": 0.15824175824175823,
175
+ "grad_norm": 0.3906334340572357,
176
+ "learning_rate": 0.00019201773835920177,
177
+ "loss": 1.0983,
178
+ "step": 24
179
+ },
180
+ {
181
+ "epoch": 0.16483516483516483,
182
+ "grad_norm": 0.3786067068576813,
183
+ "learning_rate": 0.00019157427937915744,
184
+ "loss": 1.0237,
185
+ "step": 25
186
+ },
187
+ {
188
+ "epoch": 0.17142857142857143,
189
+ "grad_norm": 0.36092478036880493,
190
+ "learning_rate": 0.00019113082039911309,
191
+ "loss": 0.9729,
192
+ "step": 26
193
+ },
194
+ {
195
+ "epoch": 0.17802197802197803,
196
+ "grad_norm": 0.27863427996635437,
197
+ "learning_rate": 0.00019068736141906876,
198
+ "loss": 0.9565,
199
+ "step": 27
200
+ },
201
+ {
202
+ "epoch": 0.18461538461538463,
203
+ "grad_norm": 0.30928313732147217,
204
+ "learning_rate": 0.0001902439024390244,
205
+ "loss": 1.0746,
206
+ "step": 28
207
+ },
208
+ {
209
+ "epoch": 0.1912087912087912,
210
+ "grad_norm": 0.3250511586666107,
211
+ "learning_rate": 0.00018980044345898005,
212
+ "loss": 0.9843,
213
+ "step": 29
214
+ },
215
+ {
216
+ "epoch": 0.1978021978021978,
217
+ "grad_norm": 0.30846866965293884,
218
+ "learning_rate": 0.00018935698447893572,
219
+ "loss": 1.0582,
220
+ "step": 30
221
+ },
222
+ {
223
+ "epoch": 0.2043956043956044,
224
+ "grad_norm": 0.3773055672645569,
225
+ "learning_rate": 0.00018891352549889136,
226
+ "loss": 0.9213,
227
+ "step": 31
228
+ },
229
+ {
230
+ "epoch": 0.210989010989011,
231
+ "grad_norm": 0.3716050386428833,
232
+ "learning_rate": 0.00018847006651884703,
233
+ "loss": 0.9804,
234
+ "step": 32
235
+ },
236
+ {
237
+ "epoch": 0.2175824175824176,
238
+ "grad_norm": 0.3420291244983673,
239
+ "learning_rate": 0.00018802660753880268,
240
+ "loss": 1.0815,
241
+ "step": 33
242
+ },
243
+ {
244
+ "epoch": 0.22417582417582418,
245
+ "grad_norm": 0.2763300836086273,
246
+ "learning_rate": 0.00018758314855875832,
247
+ "loss": 0.902,
248
+ "step": 34
249
+ },
250
+ {
251
+ "epoch": 0.23076923076923078,
252
+ "grad_norm": 0.3937534689903259,
253
+ "learning_rate": 0.00018713968957871397,
254
+ "loss": 1.1645,
255
+ "step": 35
256
+ },
257
+ {
258
+ "epoch": 0.23736263736263735,
259
+ "grad_norm": 0.27199873328208923,
260
+ "learning_rate": 0.00018669623059866964,
261
+ "loss": 0.8738,
262
+ "step": 36
263
+ },
264
+ {
265
+ "epoch": 0.24395604395604395,
266
+ "grad_norm": 0.2848569452762604,
267
+ "learning_rate": 0.00018625277161862528,
268
+ "loss": 1.0149,
269
+ "step": 37
270
+ },
271
+ {
272
+ "epoch": 0.25054945054945055,
273
+ "grad_norm": 0.31365159153938293,
274
+ "learning_rate": 0.00018580931263858095,
275
+ "loss": 0.9087,
276
+ "step": 38
277
+ },
278
+ {
279
+ "epoch": 0.2571428571428571,
280
+ "grad_norm": 0.24746054410934448,
281
+ "learning_rate": 0.0001853658536585366,
282
+ "loss": 0.9948,
283
+ "step": 39
284
+ },
285
+ {
286
+ "epoch": 0.26373626373626374,
287
+ "grad_norm": 0.23962347209453583,
288
+ "learning_rate": 0.00018492239467849224,
289
+ "loss": 1.1008,
290
+ "step": 40
291
+ },
292
+ {
293
+ "epoch": 0.2703296703296703,
294
+ "grad_norm": 0.28994685411453247,
295
+ "learning_rate": 0.0001844789356984479,
296
+ "loss": 0.915,
297
+ "step": 41
298
+ },
299
+ {
300
+ "epoch": 0.27692307692307694,
301
+ "grad_norm": 0.30804207921028137,
302
+ "learning_rate": 0.00018403547671840356,
303
+ "loss": 0.8168,
304
+ "step": 42
305
+ },
306
+ {
307
+ "epoch": 0.2835164835164835,
308
+ "grad_norm": 0.397780179977417,
309
+ "learning_rate": 0.0001835920177383592,
310
+ "loss": 1.0102,
311
+ "step": 43
312
+ },
313
+ {
314
+ "epoch": 0.29010989010989013,
315
+ "grad_norm": 0.28575780987739563,
316
+ "learning_rate": 0.00018314855875831487,
317
+ "loss": 1.0709,
318
+ "step": 44
319
+ },
320
+ {
321
+ "epoch": 0.2967032967032967,
322
+ "grad_norm": 0.2701430022716522,
323
+ "learning_rate": 0.00018270509977827052,
324
+ "loss": 0.9748,
325
+ "step": 45
326
+ },
327
+ {
328
+ "epoch": 0.3032967032967033,
329
+ "grad_norm": 0.34878647327423096,
330
+ "learning_rate": 0.00018226164079822616,
331
+ "loss": 0.9461,
332
+ "step": 46
333
+ },
334
+ {
335
+ "epoch": 0.3098901098901099,
336
+ "grad_norm": 0.29195308685302734,
337
+ "learning_rate": 0.00018181818181818183,
338
+ "loss": 0.9907,
339
+ "step": 47
340
+ },
341
+ {
342
+ "epoch": 0.31648351648351647,
343
+ "grad_norm": 0.32355818152427673,
344
+ "learning_rate": 0.00018137472283813748,
345
+ "loss": 1.0469,
346
+ "step": 48
347
+ },
348
+ {
349
+ "epoch": 0.3230769230769231,
350
+ "grad_norm": 0.3442789614200592,
351
+ "learning_rate": 0.00018093126385809312,
352
+ "loss": 1.017,
353
+ "step": 49
354
+ },
355
+ {
356
+ "epoch": 0.32967032967032966,
357
+ "grad_norm": 0.3519359827041626,
358
+ "learning_rate": 0.0001804878048780488,
359
+ "loss": 0.9013,
360
+ "step": 50
361
+ },
362
+ {
363
+ "epoch": 0.3362637362637363,
364
+ "grad_norm": 0.26735949516296387,
365
+ "learning_rate": 0.00018004434589800444,
366
+ "loss": 1.0039,
367
+ "step": 51
368
+ },
369
+ {
370
+ "epoch": 0.34285714285714286,
371
+ "grad_norm": 0.27275341749191284,
372
+ "learning_rate": 0.00017960088691796008,
373
+ "loss": 0.8377,
374
+ "step": 52
375
+ },
376
+ {
377
+ "epoch": 0.34945054945054943,
378
+ "grad_norm": 0.3131617307662964,
379
+ "learning_rate": 0.00017915742793791575,
380
+ "loss": 1.079,
381
+ "step": 53
382
+ },
383
+ {
384
+ "epoch": 0.35604395604395606,
385
+ "grad_norm": 0.3103640675544739,
386
+ "learning_rate": 0.0001787139689578714,
387
+ "loss": 1.1037,
388
+ "step": 54
389
+ },
390
+ {
391
+ "epoch": 0.3626373626373626,
392
+ "grad_norm": 0.3662891089916229,
393
+ "learning_rate": 0.00017827050997782707,
394
+ "loss": 1.2238,
395
+ "step": 55
396
+ },
397
+ {
398
+ "epoch": 0.36923076923076925,
399
+ "grad_norm": 0.31076231598854065,
400
+ "learning_rate": 0.00017782705099778271,
401
+ "loss": 1.0621,
402
+ "step": 56
403
+ },
404
+ {
405
+ "epoch": 0.3758241758241758,
406
+ "grad_norm": 0.364701509475708,
407
+ "learning_rate": 0.00017738359201773839,
408
+ "loss": 0.8895,
409
+ "step": 57
410
+ },
411
+ {
412
+ "epoch": 0.3824175824175824,
413
+ "grad_norm": 0.3279484212398529,
414
+ "learning_rate": 0.000176940133037694,
415
+ "loss": 0.8092,
416
+ "step": 58
417
+ },
418
+ {
419
+ "epoch": 0.389010989010989,
420
+ "grad_norm": 0.4195176959037781,
421
+ "learning_rate": 0.00017649667405764967,
422
+ "loss": 1.0942,
423
+ "step": 59
424
+ },
425
+ {
426
+ "epoch": 0.3956043956043956,
427
+ "grad_norm": 0.35336142778396606,
428
+ "learning_rate": 0.00017605321507760532,
429
+ "loss": 0.9458,
430
+ "step": 60
431
+ },
432
+ {
433
+ "epoch": 0.4021978021978022,
434
+ "grad_norm": 0.2668030560016632,
435
+ "learning_rate": 0.000175609756097561,
436
+ "loss": 0.7203,
437
+ "step": 61
438
+ },
439
+ {
440
+ "epoch": 0.4087912087912088,
441
+ "grad_norm": 0.2878060042858124,
442
+ "learning_rate": 0.00017516629711751663,
443
+ "loss": 0.8954,
444
+ "step": 62
445
+ },
446
+ {
447
+ "epoch": 0.4153846153846154,
448
+ "grad_norm": 0.28040236234664917,
449
+ "learning_rate": 0.0001747228381374723,
450
+ "loss": 0.847,
451
+ "step": 63
452
+ },
453
+ {
454
+ "epoch": 0.421978021978022,
455
+ "grad_norm": 0.38638436794281006,
456
+ "learning_rate": 0.00017427937915742792,
457
+ "loss": 0.9154,
458
+ "step": 64
459
+ },
460
+ {
461
+ "epoch": 0.42857142857142855,
462
+ "grad_norm": 0.3532263934612274,
463
+ "learning_rate": 0.0001738359201773836,
464
+ "loss": 0.967,
465
+ "step": 65
466
+ },
467
+ {
468
+ "epoch": 0.4351648351648352,
469
+ "grad_norm": 0.24510745704174042,
470
+ "learning_rate": 0.00017339246119733924,
471
+ "loss": 0.9775,
472
+ "step": 66
473
+ },
474
+ {
475
+ "epoch": 0.44175824175824174,
476
+ "grad_norm": 0.2761436402797699,
477
+ "learning_rate": 0.0001729490022172949,
478
+ "loss": 0.9424,
479
+ "step": 67
480
+ },
481
+ {
482
+ "epoch": 0.44835164835164837,
483
+ "grad_norm": 0.2630966901779175,
484
+ "learning_rate": 0.00017250554323725056,
485
+ "loss": 0.9213,
486
+ "step": 68
487
+ },
488
+ {
489
+ "epoch": 0.45494505494505494,
490
+ "grad_norm": 0.2421293705701828,
491
+ "learning_rate": 0.00017206208425720623,
492
+ "loss": 0.903,
493
+ "step": 69
494
+ },
495
+ {
496
+ "epoch": 0.46153846153846156,
497
+ "grad_norm": 0.3474556505680084,
498
+ "learning_rate": 0.00017161862527716187,
499
+ "loss": 1.0754,
500
+ "step": 70
501
+ },
502
+ {
503
+ "epoch": 0.46813186813186813,
504
+ "grad_norm": 0.25004228949546814,
505
+ "learning_rate": 0.00017117516629711752,
506
+ "loss": 0.9385,
507
+ "step": 71
508
+ },
509
+ {
510
+ "epoch": 0.4747252747252747,
511
+ "grad_norm": 0.3480256199836731,
512
+ "learning_rate": 0.0001707317073170732,
513
+ "loss": 0.8971,
514
+ "step": 72
515
+ },
516
+ {
517
+ "epoch": 0.48131868131868133,
518
+ "grad_norm": 0.35953742265701294,
519
+ "learning_rate": 0.00017028824833702883,
520
+ "loss": 1.0076,
521
+ "step": 73
522
+ },
523
+ {
524
+ "epoch": 0.4879120879120879,
525
+ "grad_norm": 0.2506542503833771,
526
+ "learning_rate": 0.0001698447893569845,
527
+ "loss": 0.771,
528
+ "step": 74
529
+ },
530
+ {
531
+ "epoch": 0.4945054945054945,
532
+ "grad_norm": 0.29169702529907227,
533
+ "learning_rate": 0.00016940133037694015,
534
+ "loss": 0.7205,
535
+ "step": 75
536
+ },
537
+ {
538
+ "epoch": 0.5010989010989011,
539
+ "grad_norm": 0.26952701807022095,
540
+ "learning_rate": 0.00016895787139689582,
541
+ "loss": 1.0331,
542
+ "step": 76
543
+ },
544
+ {
545
+ "epoch": 0.5076923076923077,
546
+ "grad_norm": 0.3254987895488739,
547
+ "learning_rate": 0.00016851441241685144,
548
+ "loss": 0.9197,
549
+ "step": 77
550
+ },
551
+ {
552
+ "epoch": 0.5142857142857142,
553
+ "grad_norm": 0.2873916029930115,
554
+ "learning_rate": 0.0001680709534368071,
555
+ "loss": 1.0837,
556
+ "step": 78
557
+ },
558
+ {
559
+ "epoch": 0.5208791208791209,
560
+ "grad_norm": 0.3419133424758911,
561
+ "learning_rate": 0.00016762749445676275,
562
+ "loss": 0.8816,
563
+ "step": 79
564
+ },
565
+ {
566
+ "epoch": 0.5274725274725275,
567
+ "grad_norm": 0.29397767782211304,
568
+ "learning_rate": 0.00016718403547671842,
569
+ "loss": 1.0683,
570
+ "step": 80
571
+ },
572
+ {
573
+ "epoch": 0.5340659340659341,
574
+ "grad_norm": 0.2623101472854614,
575
+ "learning_rate": 0.00016674057649667407,
576
+ "loss": 0.8472,
577
+ "step": 81
578
+ },
579
+ {
580
+ "epoch": 0.5406593406593406,
581
+ "grad_norm": 0.44186830520629883,
582
+ "learning_rate": 0.00016629711751662974,
583
+ "loss": 1.2116,
584
+ "step": 82
585
+ },
586
+ {
587
+ "epoch": 0.5472527472527473,
588
+ "grad_norm": 0.4125562906265259,
589
+ "learning_rate": 0.00016585365853658536,
590
+ "loss": 1.0062,
591
+ "step": 83
592
+ },
593
+ {
594
+ "epoch": 0.5538461538461539,
595
+ "grad_norm": 0.3349130153656006,
596
+ "learning_rate": 0.00016541019955654103,
597
+ "loss": 0.8995,
598
+ "step": 84
599
+ },
600
+ {
601
+ "epoch": 0.5604395604395604,
602
+ "grad_norm": 0.34971699118614197,
603
+ "learning_rate": 0.00016496674057649667,
604
+ "loss": 0.8694,
605
+ "step": 85
606
+ },
607
+ {
608
+ "epoch": 0.567032967032967,
609
+ "grad_norm": 0.3700663447380066,
610
+ "learning_rate": 0.00016452328159645234,
611
+ "loss": 1.0927,
612
+ "step": 86
613
+ },
614
+ {
615
+ "epoch": 0.5736263736263736,
616
+ "grad_norm": 0.28516340255737305,
617
+ "learning_rate": 0.000164079822616408,
618
+ "loss": 0.8334,
619
+ "step": 87
620
+ },
621
+ {
622
+ "epoch": 0.5802197802197803,
623
+ "grad_norm": 0.27797970175743103,
624
+ "learning_rate": 0.00016363636363636366,
625
+ "loss": 0.8108,
626
+ "step": 88
627
+ },
628
+ {
629
+ "epoch": 0.5868131868131868,
630
+ "grad_norm": 0.3791492283344269,
631
+ "learning_rate": 0.0001631929046563193,
632
+ "loss": 0.8473,
633
+ "step": 89
634
+ },
635
+ {
636
+ "epoch": 0.5934065934065934,
637
+ "grad_norm": 0.34083792567253113,
638
+ "learning_rate": 0.00016274944567627495,
639
+ "loss": 0.9353,
640
+ "step": 90
641
+ },
642
+ {
643
+ "epoch": 0.6,
644
+ "grad_norm": 0.28273823857307434,
645
+ "learning_rate": 0.0001623059866962306,
646
+ "loss": 0.8956,
647
+ "step": 91
648
+ },
649
+ {
650
+ "epoch": 0.6065934065934065,
651
+ "grad_norm": 0.3167821764945984,
652
+ "learning_rate": 0.00016186252771618626,
653
+ "loss": 0.8953,
654
+ "step": 92
655
+ },
656
+ {
657
+ "epoch": 0.6131868131868132,
658
+ "grad_norm": 0.26616188883781433,
659
+ "learning_rate": 0.0001614190687361419,
660
+ "loss": 0.8261,
661
+ "step": 93
662
+ },
663
+ {
664
+ "epoch": 0.6197802197802198,
665
+ "grad_norm": 0.237916499376297,
666
+ "learning_rate": 0.00016097560975609758,
667
+ "loss": 0.8914,
668
+ "step": 94
669
+ },
670
+ {
671
+ "epoch": 0.6263736263736264,
672
+ "grad_norm": 0.32362309098243713,
673
+ "learning_rate": 0.00016053215077605322,
674
+ "loss": 0.9295,
675
+ "step": 95
676
+ },
677
+ {
678
+ "epoch": 0.6329670329670329,
679
+ "grad_norm": 0.2910405099391937,
680
+ "learning_rate": 0.00016008869179600887,
681
+ "loss": 1.047,
682
+ "step": 96
683
+ },
684
+ {
685
+ "epoch": 0.6395604395604395,
686
+ "grad_norm": 0.279320627450943,
687
+ "learning_rate": 0.00015964523281596454,
688
+ "loss": 0.9465,
689
+ "step": 97
690
+ },
691
+ {
692
+ "epoch": 0.6461538461538462,
693
+ "grad_norm": 0.36068761348724365,
694
+ "learning_rate": 0.00015920177383592018,
695
+ "loss": 1.0782,
696
+ "step": 98
697
+ },
698
+ {
699
+ "epoch": 0.6527472527472528,
700
+ "grad_norm": 0.38116326928138733,
701
+ "learning_rate": 0.00015875831485587586,
702
+ "loss": 0.8893,
703
+ "step": 99
704
+ },
705
+ {
706
+ "epoch": 0.6593406593406593,
707
+ "grad_norm": 0.28538259863853455,
708
+ "learning_rate": 0.0001583148558758315,
709
+ "loss": 0.8015,
710
+ "step": 100
711
+ },
712
+ {
713
+ "epoch": 0.6659340659340659,
714
+ "grad_norm": 0.3541967272758484,
715
+ "learning_rate": 0.00015787139689578714,
716
+ "loss": 0.8434,
717
+ "step": 101
718
+ },
719
+ {
720
+ "epoch": 0.6725274725274726,
721
+ "grad_norm": 0.34469982981681824,
722
+ "learning_rate": 0.0001574279379157428,
723
+ "loss": 0.8324,
724
+ "step": 102
725
+ },
726
+ {
727
+ "epoch": 0.6791208791208792,
728
+ "grad_norm": 0.4213978946208954,
729
+ "learning_rate": 0.00015698447893569846,
730
+ "loss": 0.9444,
731
+ "step": 103
732
+ },
733
+ {
734
+ "epoch": 0.6857142857142857,
735
+ "grad_norm": 0.3815469741821289,
736
+ "learning_rate": 0.0001565410199556541,
737
+ "loss": 0.8776,
738
+ "step": 104
739
+ },
740
+ {
741
+ "epoch": 0.6923076923076923,
742
+ "grad_norm": 0.35397177934646606,
743
+ "learning_rate": 0.00015609756097560978,
744
+ "loss": 1.1552,
745
+ "step": 105
746
+ },
747
+ {
748
+ "epoch": 0.6989010989010989,
749
+ "grad_norm": 0.2684699594974518,
750
+ "learning_rate": 0.00015565410199556542,
751
+ "loss": 0.7798,
752
+ "step": 106
753
+ },
754
+ {
755
+ "epoch": 0.7054945054945055,
756
+ "grad_norm": 0.25741079449653625,
757
+ "learning_rate": 0.00015521064301552106,
758
+ "loss": 0.8422,
759
+ "step": 107
760
+ },
761
+ {
762
+ "epoch": 0.7120879120879121,
763
+ "grad_norm": 0.32127293944358826,
764
+ "learning_rate": 0.0001547671840354767,
765
+ "loss": 0.8322,
766
+ "step": 108
767
+ },
768
+ {
769
+ "epoch": 0.7186813186813187,
770
+ "grad_norm": 0.3340221643447876,
771
+ "learning_rate": 0.00015432372505543238,
772
+ "loss": 0.9798,
773
+ "step": 109
774
+ },
775
+ {
776
+ "epoch": 0.7252747252747253,
777
+ "grad_norm": 0.34005194902420044,
778
+ "learning_rate": 0.00015388026607538802,
779
+ "loss": 0.8661,
780
+ "step": 110
781
+ },
782
+ {
783
+ "epoch": 0.7318681318681318,
784
+ "grad_norm": 0.3739411532878876,
785
+ "learning_rate": 0.0001534368070953437,
786
+ "loss": 1.021,
787
+ "step": 111
788
+ },
789
+ {
790
+ "epoch": 0.7384615384615385,
791
+ "grad_norm": 0.3668403625488281,
792
+ "learning_rate": 0.00015299334811529934,
793
+ "loss": 0.9958,
794
+ "step": 112
795
+ },
796
+ {
797
+ "epoch": 0.7450549450549451,
798
+ "grad_norm": 0.3145362436771393,
799
+ "learning_rate": 0.00015254988913525498,
800
+ "loss": 1.0518,
801
+ "step": 113
802
+ },
803
+ {
804
+ "epoch": 0.7516483516483516,
805
+ "grad_norm": 0.3513026535511017,
806
+ "learning_rate": 0.00015210643015521066,
807
+ "loss": 1.0291,
808
+ "step": 114
809
+ },
810
+ {
811
+ "epoch": 0.7582417582417582,
812
+ "grad_norm": 0.34400007128715515,
813
+ "learning_rate": 0.0001516629711751663,
814
+ "loss": 0.9739,
815
+ "step": 115
816
+ },
817
+ {
818
+ "epoch": 0.7648351648351648,
819
+ "grad_norm": 0.3597501516342163,
820
+ "learning_rate": 0.00015121951219512197,
821
+ "loss": 1.2324,
822
+ "step": 116
823
+ },
824
+ {
825
+ "epoch": 0.7714285714285715,
826
+ "grad_norm": 0.2896723449230194,
827
+ "learning_rate": 0.00015077605321507762,
828
+ "loss": 0.8937,
829
+ "step": 117
830
+ },
831
+ {
832
+ "epoch": 0.778021978021978,
833
+ "grad_norm": 0.30057957768440247,
834
+ "learning_rate": 0.0001503325942350333,
835
+ "loss": 0.8983,
836
+ "step": 118
837
+ },
838
+ {
839
+ "epoch": 0.7846153846153846,
840
+ "grad_norm": 0.3905964195728302,
841
+ "learning_rate": 0.0001498891352549889,
842
+ "loss": 0.7167,
843
+ "step": 119
844
+ },
845
+ {
846
+ "epoch": 0.7912087912087912,
847
+ "grad_norm": 0.3202342092990875,
848
+ "learning_rate": 0.00014944567627494458,
849
+ "loss": 0.8969,
850
+ "step": 120
851
+ },
852
+ {
853
+ "epoch": 0.7978021978021979,
854
+ "grad_norm": 0.2450852394104004,
855
+ "learning_rate": 0.00014900221729490022,
856
+ "loss": 0.9203,
857
+ "step": 121
858
+ },
859
+ {
860
+ "epoch": 0.8043956043956044,
861
+ "grad_norm": 0.3147158622741699,
862
+ "learning_rate": 0.0001485587583148559,
863
+ "loss": 0.7941,
864
+ "step": 122
865
+ },
866
+ {
867
+ "epoch": 0.810989010989011,
868
+ "grad_norm": 0.34787628054618835,
869
+ "learning_rate": 0.00014811529933481154,
870
+ "loss": 1.0058,
871
+ "step": 123
872
+ },
873
+ {
874
+ "epoch": 0.8175824175824176,
875
+ "grad_norm": 0.3001445233821869,
876
+ "learning_rate": 0.0001476718403547672,
877
+ "loss": 0.8574,
878
+ "step": 124
879
+ },
880
+ {
881
+ "epoch": 0.8241758241758241,
882
+ "grad_norm": 0.3221536874771118,
883
+ "learning_rate": 0.00014722838137472282,
884
+ "loss": 1.1149,
885
+ "step": 125
886
+ },
887
+ {
888
+ "epoch": 0.8307692307692308,
889
+ "grad_norm": 0.32140639424324036,
890
+ "learning_rate": 0.0001467849223946785,
891
+ "loss": 1.1972,
892
+ "step": 126
893
+ },
894
+ {
895
+ "epoch": 0.8373626373626374,
896
+ "grad_norm": 0.30501997470855713,
897
+ "learning_rate": 0.00014634146341463414,
898
+ "loss": 0.929,
899
+ "step": 127
900
+ },
901
+ {
902
+ "epoch": 0.843956043956044,
903
+ "grad_norm": 0.3393065333366394,
904
+ "learning_rate": 0.0001458980044345898,
905
+ "loss": 0.8179,
906
+ "step": 128
907
+ },
908
+ {
909
+ "epoch": 0.8505494505494505,
910
+ "grad_norm": 0.3530517816543579,
911
+ "learning_rate": 0.00014545454545454546,
912
+ "loss": 1.0044,
913
+ "step": 129
914
+ },
915
+ {
916
+ "epoch": 0.8571428571428571,
917
+ "grad_norm": 0.29705455899238586,
918
+ "learning_rate": 0.00014501108647450113,
919
+ "loss": 0.9902,
920
+ "step": 130
921
+ },
922
+ {
923
+ "epoch": 0.8637362637362638,
924
+ "grad_norm": 0.3452480733394623,
925
+ "learning_rate": 0.00014456762749445675,
926
+ "loss": 0.9743,
927
+ "step": 131
928
+ },
929
+ {
930
+ "epoch": 0.8703296703296703,
931
+ "grad_norm": 0.2938392162322998,
932
+ "learning_rate": 0.00014412416851441242,
933
+ "loss": 0.8866,
934
+ "step": 132
935
+ },
936
+ {
937
+ "epoch": 0.8769230769230769,
938
+ "grad_norm": 0.30601850152015686,
939
+ "learning_rate": 0.00014368070953436806,
940
+ "loss": 0.9861,
941
+ "step": 133
942
+ },
943
+ {
944
+ "epoch": 0.8835164835164835,
945
+ "grad_norm": 0.28590455651283264,
946
+ "learning_rate": 0.00014323725055432373,
947
+ "loss": 0.8338,
948
+ "step": 134
949
+ },
950
+ {
951
+ "epoch": 0.8901098901098901,
952
+ "grad_norm": 0.2874011695384979,
953
+ "learning_rate": 0.00014279379157427938,
954
+ "loss": 0.9952,
955
+ "step": 135
956
+ },
957
+ {
958
+ "epoch": 0.8967032967032967,
959
+ "grad_norm": 0.3361506462097168,
960
+ "learning_rate": 0.00014235033259423505,
961
+ "loss": 1.0219,
962
+ "step": 136
963
+ },
964
+ {
965
+ "epoch": 0.9032967032967033,
966
+ "grad_norm": 0.3574809730052948,
967
+ "learning_rate": 0.0001419068736141907,
968
+ "loss": 0.8814,
969
+ "step": 137
970
+ },
971
+ {
972
+ "epoch": 0.9098901098901099,
973
+ "grad_norm": 0.4311088025569916,
974
+ "learning_rate": 0.00014146341463414634,
975
+ "loss": 0.9013,
976
+ "step": 138
977
+ },
978
+ {
979
+ "epoch": 0.9164835164835164,
980
+ "grad_norm": 0.26233023405075073,
981
+ "learning_rate": 0.000141019955654102,
982
+ "loss": 0.8736,
983
+ "step": 139
984
+ },
985
+ {
986
+ "epoch": 0.9230769230769231,
987
+ "grad_norm": 0.35940396785736084,
988
+ "learning_rate": 0.00014057649667405765,
989
+ "loss": 0.9749,
990
+ "step": 140
991
+ },
992
+ {
993
+ "epoch": 0.9296703296703297,
994
+ "grad_norm": 0.27149611711502075,
995
+ "learning_rate": 0.00014013303769401332,
996
+ "loss": 0.922,
997
+ "step": 141
998
+ },
999
+ {
1000
+ "epoch": 0.9362637362637363,
1001
+ "grad_norm": 0.4147508442401886,
1002
+ "learning_rate": 0.00013968957871396897,
1003
+ "loss": 1.0781,
1004
+ "step": 142
1005
+ },
1006
+ {
1007
+ "epoch": 0.9428571428571428,
1008
+ "grad_norm": 0.295341432094574,
1009
+ "learning_rate": 0.00013924611973392464,
1010
+ "loss": 0.9529,
1011
+ "step": 143
1012
+ },
1013
+ {
1014
+ "epoch": 0.9494505494505494,
1015
+ "grad_norm": 0.36334657669067383,
1016
+ "learning_rate": 0.00013880266075388026,
1017
+ "loss": 0.8085,
1018
+ "step": 144
1019
+ },
1020
+ {
1021
+ "epoch": 0.9560439560439561,
1022
+ "grad_norm": 0.24359752237796783,
1023
+ "learning_rate": 0.00013835920177383593,
1024
+ "loss": 0.7036,
1025
+ "step": 145
1026
+ },
1027
+ {
1028
+ "epoch": 0.9626373626373627,
1029
+ "grad_norm": 0.3110310733318329,
1030
+ "learning_rate": 0.00013791574279379157,
1031
+ "loss": 0.7797,
1032
+ "step": 146
1033
+ },
1034
+ {
1035
+ "epoch": 0.9692307692307692,
1036
+ "grad_norm": 0.3413989841938019,
1037
+ "learning_rate": 0.00013747228381374724,
1038
+ "loss": 1.0027,
1039
+ "step": 147
1040
+ },
1041
+ {
1042
+ "epoch": 0.9758241758241758,
1043
+ "grad_norm": 0.2888753116130829,
1044
+ "learning_rate": 0.0001370288248337029,
1045
+ "loss": 0.8844,
1046
+ "step": 148
1047
+ },
1048
+ {
1049
+ "epoch": 0.9824175824175824,
1050
+ "grad_norm": 0.32249295711517334,
1051
+ "learning_rate": 0.00013658536585365856,
1052
+ "loss": 0.8261,
1053
+ "step": 149
1054
+ },
1055
+ {
1056
+ "epoch": 0.989010989010989,
1057
+ "grad_norm": 0.4273090660572052,
1058
+ "learning_rate": 0.00013614190687361418,
1059
+ "loss": 1.0066,
1060
+ "step": 150
1061
+ },
1062
+ {
1063
+ "epoch": 0.9956043956043956,
1064
+ "grad_norm": 0.28998544812202454,
1065
+ "learning_rate": 0.00013569844789356985,
1066
+ "loss": 0.8485,
1067
+ "step": 151
1068
+ },
1069
+ {
1070
+ "epoch": 1.0,
1071
+ "grad_norm": 0.4690309762954712,
1072
+ "learning_rate": 0.0001352549889135255,
1073
+ "loss": 0.6486,
1074
+ "step": 152
1075
+ },
1076
+ {
1077
+ "epoch": 1.0065934065934066,
1078
+ "grad_norm": 0.3045438528060913,
1079
+ "learning_rate": 0.00013481152993348116,
1080
+ "loss": 0.8676,
1081
+ "step": 153
1082
+ },
1083
+ {
1084
+ "epoch": 1.0131868131868131,
1085
+ "grad_norm": 0.3148064613342285,
1086
+ "learning_rate": 0.0001343680709534368,
1087
+ "loss": 0.9665,
1088
+ "step": 154
1089
+ },
1090
+ {
1091
+ "epoch": 1.0197802197802197,
1092
+ "grad_norm": 0.32930025458335876,
1093
+ "learning_rate": 0.00013392461197339248,
1094
+ "loss": 0.8087,
1095
+ "step": 155
1096
+ },
1097
+ {
1098
+ "epoch": 1.0263736263736263,
1099
+ "grad_norm": 0.2816562354564667,
1100
+ "learning_rate": 0.00013348115299334812,
1101
+ "loss": 0.7944,
1102
+ "step": 156
1103
+ },
1104
+ {
1105
+ "epoch": 1.032967032967033,
1106
+ "grad_norm": 0.3011133074760437,
1107
+ "learning_rate": 0.00013303769401330377,
1108
+ "loss": 0.7996,
1109
+ "step": 157
1110
+ },
1111
+ {
1112
+ "epoch": 1.0395604395604396,
1113
+ "grad_norm": 0.3297262191772461,
1114
+ "learning_rate": 0.00013259423503325944,
1115
+ "loss": 0.8268,
1116
+ "step": 158
1117
+ },
1118
+ {
1119
+ "epoch": 1.0461538461538462,
1120
+ "grad_norm": 0.3308207392692566,
1121
+ "learning_rate": 0.00013215077605321509,
1122
+ "loss": 0.7508,
1123
+ "step": 159
1124
+ },
1125
+ {
1126
+ "epoch": 1.0527472527472528,
1127
+ "grad_norm": 0.3697322607040405,
1128
+ "learning_rate": 0.00013170731707317076,
1129
+ "loss": 0.7181,
1130
+ "step": 160
1131
+ },
1132
+ {
1133
+ "epoch": 1.0593406593406594,
1134
+ "grad_norm": 0.3329128921031952,
1135
+ "learning_rate": 0.0001312638580931264,
1136
+ "loss": 0.7619,
1137
+ "step": 161
1138
+ },
1139
+ {
1140
+ "epoch": 1.065934065934066,
1141
+ "grad_norm": 0.36436977982521057,
1142
+ "learning_rate": 0.00013082039911308205,
1143
+ "loss": 0.7969,
1144
+ "step": 162
1145
+ },
1146
+ {
1147
+ "epoch": 1.0725274725274725,
1148
+ "grad_norm": 0.33429184556007385,
1149
+ "learning_rate": 0.0001303769401330377,
1150
+ "loss": 1.0637,
1151
+ "step": 163
1152
+ },
1153
+ {
1154
+ "epoch": 1.079120879120879,
1155
+ "grad_norm": 0.4259260892868042,
1156
+ "learning_rate": 0.00012993348115299336,
1157
+ "loss": 0.968,
1158
+ "step": 164
1159
+ },
1160
+ {
1161
+ "epoch": 1.0857142857142856,
1162
+ "grad_norm": 0.3352951109409332,
1163
+ "learning_rate": 0.000129490022172949,
1164
+ "loss": 0.8191,
1165
+ "step": 165
1166
+ },
1167
+ {
1168
+ "epoch": 1.0923076923076924,
1169
+ "grad_norm": 0.4135381579399109,
1170
+ "learning_rate": 0.00012904656319290468,
1171
+ "loss": 0.9858,
1172
+ "step": 166
1173
+ },
1174
+ {
1175
+ "epoch": 1.098901098901099,
1176
+ "grad_norm": 0.3486995995044708,
1177
+ "learning_rate": 0.00012860310421286032,
1178
+ "loss": 0.8626,
1179
+ "step": 167
1180
+ },
1181
+ {
1182
+ "epoch": 1.1054945054945056,
1183
+ "grad_norm": 0.37806546688079834,
1184
+ "learning_rate": 0.00012815964523281597,
1185
+ "loss": 0.9596,
1186
+ "step": 168
1187
+ },
1188
+ {
1189
+ "epoch": 1.1120879120879121,
1190
+ "grad_norm": 0.3310850262641907,
1191
+ "learning_rate": 0.0001277161862527716,
1192
+ "loss": 0.9345,
1193
+ "step": 169
1194
+ },
1195
+ {
1196
+ "epoch": 1.1186813186813187,
1197
+ "grad_norm": 0.3593229651451111,
1198
+ "learning_rate": 0.00012727272727272728,
1199
+ "loss": 0.9171,
1200
+ "step": 170
1201
+ },
1202
+ {
1203
+ "epoch": 1.1252747252747253,
1204
+ "grad_norm": 0.38787880539894104,
1205
+ "learning_rate": 0.00012682926829268293,
1206
+ "loss": 0.8608,
1207
+ "step": 171
1208
+ },
1209
+ {
1210
+ "epoch": 1.1318681318681318,
1211
+ "grad_norm": 0.35755735635757446,
1212
+ "learning_rate": 0.0001263858093126386,
1213
+ "loss": 0.7518,
1214
+ "step": 172
1215
+ },
1216
+ {
1217
+ "epoch": 1.1384615384615384,
1218
+ "grad_norm": 0.45123910903930664,
1219
+ "learning_rate": 0.00012594235033259424,
1220
+ "loss": 0.8825,
1221
+ "step": 173
1222
+ },
1223
+ {
1224
+ "epoch": 1.145054945054945,
1225
+ "grad_norm": 0.3731641471385956,
1226
+ "learning_rate": 0.00012549889135254989,
1227
+ "loss": 0.9151,
1228
+ "step": 174
1229
+ },
1230
+ {
1231
+ "epoch": 1.1516483516483516,
1232
+ "grad_norm": 0.4211123287677765,
1233
+ "learning_rate": 0.00012505543237250553,
1234
+ "loss": 0.9073,
1235
+ "step": 175
1236
+ },
1237
+ {
1238
+ "epoch": 1.1582417582417581,
1239
+ "grad_norm": 0.3269520103931427,
1240
+ "learning_rate": 0.0001246119733924612,
1241
+ "loss": 0.7488,
1242
+ "step": 176
1243
+ },
1244
+ {
1245
+ "epoch": 1.164835164835165,
1246
+ "grad_norm": 0.36462828516960144,
1247
+ "learning_rate": 0.00012416851441241685,
1248
+ "loss": 0.8809,
1249
+ "step": 177
1250
+ },
1251
+ {
1252
+ "epoch": 1.1714285714285715,
1253
+ "grad_norm": 0.36362966895103455,
1254
+ "learning_rate": 0.00012372505543237252,
1255
+ "loss": 0.8035,
1256
+ "step": 178
1257
+ },
1258
+ {
1259
+ "epoch": 1.178021978021978,
1260
+ "grad_norm": 0.3671634793281555,
1261
+ "learning_rate": 0.00012328159645232816,
1262
+ "loss": 0.9194,
1263
+ "step": 179
1264
+ },
1265
+ {
1266
+ "epoch": 1.1846153846153846,
1267
+ "grad_norm": 0.3457624018192291,
1268
+ "learning_rate": 0.0001228381374722838,
1269
+ "loss": 0.7065,
1270
+ "step": 180
1271
+ },
1272
+ {
1273
+ "epoch": 1.1912087912087912,
1274
+ "grad_norm": 0.4401772618293762,
1275
+ "learning_rate": 0.00012239467849223948,
1276
+ "loss": 0.9267,
1277
+ "step": 181
1278
+ },
1279
+ {
1280
+ "epoch": 1.1978021978021978,
1281
+ "grad_norm": 0.4606243371963501,
1282
+ "learning_rate": 0.00012195121951219512,
1283
+ "loss": 0.836,
1284
+ "step": 182
1285
+ },
1286
+ {
1287
+ "epoch": 1.2043956043956043,
1288
+ "grad_norm": 0.3353036940097809,
1289
+ "learning_rate": 0.00012150776053215078,
1290
+ "loss": 0.6218,
1291
+ "step": 183
1292
+ },
1293
+ {
1294
+ "epoch": 1.210989010989011,
1295
+ "grad_norm": 0.4171563684940338,
1296
+ "learning_rate": 0.00012106430155210644,
1297
+ "loss": 0.7914,
1298
+ "step": 184
1299
+ },
1300
+ {
1301
+ "epoch": 1.2175824175824177,
1302
+ "grad_norm": 0.3640008270740509,
1303
+ "learning_rate": 0.0001206208425720621,
1304
+ "loss": 0.8632,
1305
+ "step": 185
1306
+ },
1307
+ {
1308
+ "epoch": 1.2241758241758243,
1309
+ "grad_norm": 0.43573465943336487,
1310
+ "learning_rate": 0.00012017738359201774,
1311
+ "loss": 0.8191,
1312
+ "step": 186
1313
+ },
1314
+ {
1315
+ "epoch": 1.2307692307692308,
1316
+ "grad_norm": 0.3201373219490051,
1317
+ "learning_rate": 0.0001197339246119734,
1318
+ "loss": 0.7808,
1319
+ "step": 187
1320
+ },
1321
+ {
1322
+ "epoch": 1.2373626373626374,
1323
+ "grad_norm": 0.403213769197464,
1324
+ "learning_rate": 0.00011929046563192906,
1325
+ "loss": 0.9004,
1326
+ "step": 188
1327
+ },
1328
+ {
1329
+ "epoch": 1.243956043956044,
1330
+ "grad_norm": 0.4063056707382202,
1331
+ "learning_rate": 0.00011884700665188471,
1332
+ "loss": 0.9791,
1333
+ "step": 189
1334
+ },
1335
+ {
1336
+ "epoch": 1.2505494505494505,
1337
+ "grad_norm": 0.4900030195713043,
1338
+ "learning_rate": 0.00011840354767184036,
1339
+ "loss": 0.8013,
1340
+ "step": 190
1341
+ },
1342
+ {
1343
+ "epoch": 1.2571428571428571,
1344
+ "grad_norm": 0.49652716517448425,
1345
+ "learning_rate": 0.00011796008869179602,
1346
+ "loss": 0.9993,
1347
+ "step": 191
1348
+ },
1349
+ {
1350
+ "epoch": 1.2637362637362637,
1351
+ "grad_norm": 0.4425002634525299,
1352
+ "learning_rate": 0.00011751662971175166,
1353
+ "loss": 0.8854,
1354
+ "step": 192
1355
+ },
1356
+ {
1357
+ "epoch": 1.2703296703296703,
1358
+ "grad_norm": 0.46226751804351807,
1359
+ "learning_rate": 0.00011707317073170732,
1360
+ "loss": 0.9893,
1361
+ "step": 193
1362
+ },
1363
+ {
1364
+ "epoch": 1.2769230769230768,
1365
+ "grad_norm": 0.3779703378677368,
1366
+ "learning_rate": 0.00011662971175166298,
1367
+ "loss": 0.7875,
1368
+ "step": 194
1369
+ },
1370
+ {
1371
+ "epoch": 1.2835164835164834,
1372
+ "grad_norm": 0.4313388168811798,
1373
+ "learning_rate": 0.00011618625277161863,
1374
+ "loss": 0.7672,
1375
+ "step": 195
1376
+ },
1377
+ {
1378
+ "epoch": 1.2901098901098902,
1379
+ "grad_norm": 0.36810222268104553,
1380
+ "learning_rate": 0.00011574279379157429,
1381
+ "loss": 0.6342,
1382
+ "step": 196
1383
+ },
1384
+ {
1385
+ "epoch": 1.2967032967032968,
1386
+ "grad_norm": 0.37219274044036865,
1387
+ "learning_rate": 0.00011529933481152995,
1388
+ "loss": 0.8084,
1389
+ "step": 197
1390
+ },
1391
+ {
1392
+ "epoch": 1.3032967032967033,
1393
+ "grad_norm": 0.4840892553329468,
1394
+ "learning_rate": 0.00011485587583148558,
1395
+ "loss": 0.804,
1396
+ "step": 198
1397
+ },
1398
+ {
1399
+ "epoch": 1.30989010989011,
1400
+ "grad_norm": 0.4374985694885254,
1401
+ "learning_rate": 0.00011441241685144124,
1402
+ "loss": 0.8546,
1403
+ "step": 199
1404
+ },
1405
+ {
1406
+ "epoch": 1.3164835164835165,
1407
+ "grad_norm": 0.3962724208831787,
1408
+ "learning_rate": 0.0001139689578713969,
1409
+ "loss": 0.7414,
1410
+ "step": 200
1411
+ },
1412
+ {
1413
+ "epoch": 1.323076923076923,
1414
+ "grad_norm": 0.37382033467292786,
1415
+ "learning_rate": 0.00011352549889135255,
1416
+ "loss": 0.8653,
1417
+ "step": 201
1418
+ },
1419
+ {
1420
+ "epoch": 1.3296703296703296,
1421
+ "grad_norm": 0.44277113676071167,
1422
+ "learning_rate": 0.00011308203991130821,
1423
+ "loss": 0.8241,
1424
+ "step": 202
1425
+ },
1426
+ {
1427
+ "epoch": 1.3362637362637364,
1428
+ "grad_norm": 0.46842196583747864,
1429
+ "learning_rate": 0.00011263858093126387,
1430
+ "loss": 0.7964,
1431
+ "step": 203
1432
+ },
1433
+ {
1434
+ "epoch": 1.342857142857143,
1435
+ "grad_norm": 0.4144313931465149,
1436
+ "learning_rate": 0.00011219512195121953,
1437
+ "loss": 0.7453,
1438
+ "step": 204
1439
+ },
1440
+ {
1441
+ "epoch": 1.3494505494505495,
1442
+ "grad_norm": 0.4482251703739166,
1443
+ "learning_rate": 0.00011175166297117516,
1444
+ "loss": 0.9691,
1445
+ "step": 205
1446
+ },
1447
+ {
1448
+ "epoch": 1.3560439560439561,
1449
+ "grad_norm": 0.41152456402778625,
1450
+ "learning_rate": 0.00011130820399113082,
1451
+ "loss": 0.7846,
1452
+ "step": 206
1453
+ },
1454
+ {
1455
+ "epoch": 1.3626373626373627,
1456
+ "grad_norm": 0.4497469961643219,
1457
+ "learning_rate": 0.00011086474501108647,
1458
+ "loss": 1.001,
1459
+ "step": 207
1460
+ },
1461
+ {
1462
+ "epoch": 1.3692307692307693,
1463
+ "grad_norm": 0.45057448744773865,
1464
+ "learning_rate": 0.00011042128603104213,
1465
+ "loss": 0.8659,
1466
+ "step": 208
1467
+ },
1468
+ {
1469
+ "epoch": 1.3758241758241758,
1470
+ "grad_norm": 0.4924719035625458,
1471
+ "learning_rate": 0.00010997782705099779,
1472
+ "loss": 0.9199,
1473
+ "step": 209
1474
+ },
1475
+ {
1476
+ "epoch": 1.3824175824175824,
1477
+ "grad_norm": 0.4531312584877014,
1478
+ "learning_rate": 0.00010953436807095345,
1479
+ "loss": 0.9154,
1480
+ "step": 210
1481
+ },
1482
+ {
1483
+ "epoch": 1.389010989010989,
1484
+ "grad_norm": 0.43056848645210266,
1485
+ "learning_rate": 0.00010909090909090909,
1486
+ "loss": 0.8943,
1487
+ "step": 211
1488
+ },
1489
+ {
1490
+ "epoch": 1.3956043956043955,
1491
+ "grad_norm": 0.4362466037273407,
1492
+ "learning_rate": 0.00010864745011086475,
1493
+ "loss": 0.6209,
1494
+ "step": 212
1495
+ },
1496
+ {
1497
+ "epoch": 1.402197802197802,
1498
+ "grad_norm": 0.5599644780158997,
1499
+ "learning_rate": 0.00010820399113082041,
1500
+ "loss": 0.8043,
1501
+ "step": 213
1502
+ },
1503
+ {
1504
+ "epoch": 1.4087912087912087,
1505
+ "grad_norm": 0.38885924220085144,
1506
+ "learning_rate": 0.00010776053215077607,
1507
+ "loss": 0.8007,
1508
+ "step": 214
1509
+ },
1510
+ {
1511
+ "epoch": 1.4153846153846155,
1512
+ "grad_norm": 0.4377254843711853,
1513
+ "learning_rate": 0.00010731707317073172,
1514
+ "loss": 0.8852,
1515
+ "step": 215
1516
+ },
1517
+ {
1518
+ "epoch": 1.421978021978022,
1519
+ "grad_norm": 0.3999001383781433,
1520
+ "learning_rate": 0.00010687361419068738,
1521
+ "loss": 0.9147,
1522
+ "step": 216
1523
+ },
1524
+ {
1525
+ "epoch": 1.4285714285714286,
1526
+ "grad_norm": 0.46440982818603516,
1527
+ "learning_rate": 0.00010643015521064301,
1528
+ "loss": 0.8844,
1529
+ "step": 217
1530
+ },
1531
+ {
1532
+ "epoch": 1.4351648351648352,
1533
+ "grad_norm": 0.46195998787879944,
1534
+ "learning_rate": 0.00010598669623059867,
1535
+ "loss": 0.7938,
1536
+ "step": 218
1537
+ },
1538
+ {
1539
+ "epoch": 1.4417582417582417,
1540
+ "grad_norm": 0.38602715730667114,
1541
+ "learning_rate": 0.00010554323725055433,
1542
+ "loss": 0.6682,
1543
+ "step": 219
1544
+ },
1545
+ {
1546
+ "epoch": 1.4483516483516483,
1547
+ "grad_norm": 0.4990112781524658,
1548
+ "learning_rate": 0.00010509977827050999,
1549
+ "loss": 1.0977,
1550
+ "step": 220
1551
+ },
1552
+ {
1553
+ "epoch": 1.4549450549450549,
1554
+ "grad_norm": 0.3537238836288452,
1555
+ "learning_rate": 0.00010465631929046564,
1556
+ "loss": 0.7534,
1557
+ "step": 221
1558
+ },
1559
+ {
1560
+ "epoch": 1.4615384615384617,
1561
+ "grad_norm": 0.5449821949005127,
1562
+ "learning_rate": 0.0001042128603104213,
1563
+ "loss": 1.017,
1564
+ "step": 222
1565
+ },
1566
+ {
1567
+ "epoch": 1.4681318681318682,
1568
+ "grad_norm": 0.44483187794685364,
1569
+ "learning_rate": 0.00010376940133037693,
1570
+ "loss": 0.8461,
1571
+ "step": 223
1572
+ },
1573
+ {
1574
+ "epoch": 1.4747252747252748,
1575
+ "grad_norm": 0.459046334028244,
1576
+ "learning_rate": 0.00010332594235033259,
1577
+ "loss": 0.8609,
1578
+ "step": 224
1579
+ },
1580
+ {
1581
+ "epoch": 1.4813186813186814,
1582
+ "grad_norm": 0.4648573100566864,
1583
+ "learning_rate": 0.00010288248337028825,
1584
+ "loss": 0.7077,
1585
+ "step": 225
1586
+ },
1587
+ {
1588
+ "epoch": 1.487912087912088,
1589
+ "grad_norm": 0.46832260489463806,
1590
+ "learning_rate": 0.0001024390243902439,
1591
+ "loss": 0.995,
1592
+ "step": 226
1593
+ },
1594
+ {
1595
+ "epoch": 1.4945054945054945,
1596
+ "grad_norm": 0.5647684335708618,
1597
+ "learning_rate": 0.00010199556541019956,
1598
+ "loss": 0.9797,
1599
+ "step": 227
1600
+ },
1601
+ {
1602
+ "epoch": 1.501098901098901,
1603
+ "grad_norm": 0.3861806094646454,
1604
+ "learning_rate": 0.00010155210643015522,
1605
+ "loss": 0.8115,
1606
+ "step": 228
1607
+ },
1608
+ {
1609
+ "epoch": 1.5076923076923077,
1610
+ "grad_norm": 0.4496518671512604,
1611
+ "learning_rate": 0.00010110864745011087,
1612
+ "loss": 0.8522,
1613
+ "step": 229
1614
+ },
1615
+ {
1616
+ "epoch": 1.5142857142857142,
1617
+ "grad_norm": 0.428604394197464,
1618
+ "learning_rate": 0.00010066518847006652,
1619
+ "loss": 0.8554,
1620
+ "step": 230
1621
+ },
1622
+ {
1623
+ "epoch": 1.5208791208791208,
1624
+ "grad_norm": 0.46109339594841003,
1625
+ "learning_rate": 0.00010022172949002218,
1626
+ "loss": 0.9584,
1627
+ "step": 231
1628
+ },
1629
+ {
1630
+ "epoch": 1.5274725274725274,
1631
+ "grad_norm": 0.5141985416412354,
1632
+ "learning_rate": 9.977827050997783e-05,
1633
+ "loss": 0.9228,
1634
+ "step": 232
1635
+ },
1636
+ {
1637
+ "epoch": 1.534065934065934,
1638
+ "grad_norm": 0.49423670768737793,
1639
+ "learning_rate": 9.933481152993348e-05,
1640
+ "loss": 0.797,
1641
+ "step": 233
1642
+ },
1643
+ {
1644
+ "epoch": 1.5406593406593405,
1645
+ "grad_norm": 0.47565293312072754,
1646
+ "learning_rate": 9.889135254988914e-05,
1647
+ "loss": 0.886,
1648
+ "step": 234
1649
+ },
1650
+ {
1651
+ "epoch": 1.5472527472527473,
1652
+ "grad_norm": 0.4218743145465851,
1653
+ "learning_rate": 9.84478935698448e-05,
1654
+ "loss": 0.8496,
1655
+ "step": 235
1656
+ },
1657
+ {
1658
+ "epoch": 1.5538461538461539,
1659
+ "grad_norm": 0.45972034335136414,
1660
+ "learning_rate": 9.800443458980046e-05,
1661
+ "loss": 0.7161,
1662
+ "step": 236
1663
+ },
1664
+ {
1665
+ "epoch": 1.5604395604395604,
1666
+ "grad_norm": 0.5325828194618225,
1667
+ "learning_rate": 9.75609756097561e-05,
1668
+ "loss": 0.8005,
1669
+ "step": 237
1670
+ },
1671
+ {
1672
+ "epoch": 1.567032967032967,
1673
+ "grad_norm": 0.4783444404602051,
1674
+ "learning_rate": 9.711751662971176e-05,
1675
+ "loss": 0.8983,
1676
+ "step": 238
1677
+ },
1678
+ {
1679
+ "epoch": 1.5736263736263736,
1680
+ "grad_norm": 0.48973003029823303,
1681
+ "learning_rate": 9.667405764966742e-05,
1682
+ "loss": 0.8455,
1683
+ "step": 239
1684
+ },
1685
+ {
1686
+ "epoch": 1.5802197802197804,
1687
+ "grad_norm": 0.4571506977081299,
1688
+ "learning_rate": 9.623059866962306e-05,
1689
+ "loss": 0.8023,
1690
+ "step": 240
1691
+ },
1692
+ {
1693
+ "epoch": 1.586813186813187,
1694
+ "grad_norm": 0.40492597222328186,
1695
+ "learning_rate": 9.578713968957872e-05,
1696
+ "loss": 0.7615,
1697
+ "step": 241
1698
+ },
1699
+ {
1700
+ "epoch": 1.5934065934065935,
1701
+ "grad_norm": 0.44703274965286255,
1702
+ "learning_rate": 9.534368070953438e-05,
1703
+ "loss": 0.8295,
1704
+ "step": 242
1705
+ },
1706
+ {
1707
+ "epoch": 1.6,
1708
+ "grad_norm": 0.46830523014068604,
1709
+ "learning_rate": 9.490022172949002e-05,
1710
+ "loss": 0.7677,
1711
+ "step": 243
1712
+ },
1713
+ {
1714
+ "epoch": 1.6065934065934067,
1715
+ "grad_norm": 0.5389837622642517,
1716
+ "learning_rate": 9.445676274944568e-05,
1717
+ "loss": 0.929,
1718
+ "step": 244
1719
+ },
1720
+ {
1721
+ "epoch": 1.6131868131868132,
1722
+ "grad_norm": 0.4897559583187103,
1723
+ "learning_rate": 9.401330376940134e-05,
1724
+ "loss": 0.7929,
1725
+ "step": 245
1726
+ },
1727
+ {
1728
+ "epoch": 1.6197802197802198,
1729
+ "grad_norm": 0.48635751008987427,
1730
+ "learning_rate": 9.356984478935698e-05,
1731
+ "loss": 0.8176,
1732
+ "step": 246
1733
+ },
1734
+ {
1735
+ "epoch": 1.6263736263736264,
1736
+ "grad_norm": 0.5070086717605591,
1737
+ "learning_rate": 9.312638580931264e-05,
1738
+ "loss": 0.8988,
1739
+ "step": 247
1740
+ },
1741
+ {
1742
+ "epoch": 1.632967032967033,
1743
+ "grad_norm": 0.5040110945701599,
1744
+ "learning_rate": 9.26829268292683e-05,
1745
+ "loss": 0.9827,
1746
+ "step": 248
1747
+ },
1748
+ {
1749
+ "epoch": 1.6395604395604395,
1750
+ "grad_norm": 0.4893195331096649,
1751
+ "learning_rate": 9.223946784922394e-05,
1752
+ "loss": 0.9108,
1753
+ "step": 249
1754
+ },
1755
+ {
1756
+ "epoch": 1.646153846153846,
1757
+ "grad_norm": 0.5183725953102112,
1758
+ "learning_rate": 9.17960088691796e-05,
1759
+ "loss": 1.0375,
1760
+ "step": 250
1761
+ },
1762
+ {
1763
+ "epoch": 1.6527472527472526,
1764
+ "grad_norm": 0.5050914287567139,
1765
+ "learning_rate": 9.135254988913526e-05,
1766
+ "loss": 0.8868,
1767
+ "step": 251
1768
+ },
1769
+ {
1770
+ "epoch": 1.6593406593406592,
1771
+ "grad_norm": 0.6539065837860107,
1772
+ "learning_rate": 9.090909090909092e-05,
1773
+ "loss": 0.919,
1774
+ "step": 252
1775
+ },
1776
+ {
1777
+ "epoch": 1.6659340659340658,
1778
+ "grad_norm": 0.5070188045501709,
1779
+ "learning_rate": 9.046563192904656e-05,
1780
+ "loss": 0.8922,
1781
+ "step": 253
1782
+ },
1783
+ {
1784
+ "epoch": 1.6725274725274726,
1785
+ "grad_norm": 0.5404043197631836,
1786
+ "learning_rate": 9.002217294900222e-05,
1787
+ "loss": 0.9583,
1788
+ "step": 254
1789
+ },
1790
+ {
1791
+ "epoch": 1.6791208791208792,
1792
+ "grad_norm": 0.5274918079376221,
1793
+ "learning_rate": 8.957871396895788e-05,
1794
+ "loss": 0.9918,
1795
+ "step": 255
1796
+ },
1797
+ {
1798
+ "epoch": 1.6857142857142857,
1799
+ "grad_norm": 0.5713817477226257,
1800
+ "learning_rate": 8.913525498891354e-05,
1801
+ "loss": 0.7026,
1802
+ "step": 256
1803
+ },
1804
+ {
1805
+ "epoch": 1.6923076923076923,
1806
+ "grad_norm": 0.4875091314315796,
1807
+ "learning_rate": 8.869179600886919e-05,
1808
+ "loss": 0.7633,
1809
+ "step": 257
1810
+ },
1811
+ {
1812
+ "epoch": 1.6989010989010989,
1813
+ "grad_norm": 0.4186699688434601,
1814
+ "learning_rate": 8.824833702882484e-05,
1815
+ "loss": 0.8017,
1816
+ "step": 258
1817
+ },
1818
+ {
1819
+ "epoch": 1.7054945054945057,
1820
+ "grad_norm": 0.4443645477294922,
1821
+ "learning_rate": 8.78048780487805e-05,
1822
+ "loss": 0.6736,
1823
+ "step": 259
1824
+ },
1825
+ {
1826
+ "epoch": 1.7120879120879122,
1827
+ "grad_norm": 0.4955357611179352,
1828
+ "learning_rate": 8.736141906873615e-05,
1829
+ "loss": 0.7624,
1830
+ "step": 260
1831
+ },
1832
+ {
1833
+ "epoch": 1.7186813186813188,
1834
+ "grad_norm": 0.4375542104244232,
1835
+ "learning_rate": 8.69179600886918e-05,
1836
+ "loss": 0.7421,
1837
+ "step": 261
1838
+ },
1839
+ {
1840
+ "epoch": 1.7252747252747254,
1841
+ "grad_norm": 0.47112950682640076,
1842
+ "learning_rate": 8.647450110864746e-05,
1843
+ "loss": 0.8486,
1844
+ "step": 262
1845
+ },
1846
+ {
1847
+ "epoch": 1.731868131868132,
1848
+ "grad_norm": 0.6528114676475525,
1849
+ "learning_rate": 8.603104212860311e-05,
1850
+ "loss": 0.7325,
1851
+ "step": 263
1852
+ },
1853
+ {
1854
+ "epoch": 1.7384615384615385,
1855
+ "grad_norm": 0.46200332045555115,
1856
+ "learning_rate": 8.558758314855876e-05,
1857
+ "loss": 0.8528,
1858
+ "step": 264
1859
+ },
1860
+ {
1861
+ "epoch": 1.745054945054945,
1862
+ "grad_norm": 0.574214518070221,
1863
+ "learning_rate": 8.514412416851442e-05,
1864
+ "loss": 0.7978,
1865
+ "step": 265
1866
+ },
1867
+ {
1868
+ "epoch": 1.7516483516483516,
1869
+ "grad_norm": 0.4962877333164215,
1870
+ "learning_rate": 8.470066518847007e-05,
1871
+ "loss": 0.8764,
1872
+ "step": 266
1873
+ },
1874
+ {
1875
+ "epoch": 1.7582417582417582,
1876
+ "grad_norm": 0.4789123237133026,
1877
+ "learning_rate": 8.425720620842572e-05,
1878
+ "loss": 0.8737,
1879
+ "step": 267
1880
+ },
1881
+ {
1882
+ "epoch": 1.7648351648351648,
1883
+ "grad_norm": 0.5246762037277222,
1884
+ "learning_rate": 8.381374722838138e-05,
1885
+ "loss": 0.8024,
1886
+ "step": 268
1887
+ },
1888
+ {
1889
+ "epoch": 1.7714285714285714,
1890
+ "grad_norm": 0.41688671708106995,
1891
+ "learning_rate": 8.337028824833703e-05,
1892
+ "loss": 0.5601,
1893
+ "step": 269
1894
+ },
1895
+ {
1896
+ "epoch": 1.778021978021978,
1897
+ "grad_norm": 0.4610651433467865,
1898
+ "learning_rate": 8.292682926829268e-05,
1899
+ "loss": 0.6669,
1900
+ "step": 270
1901
+ },
1902
+ {
1903
+ "epoch": 1.7846153846153845,
1904
+ "grad_norm": 0.5566967129707336,
1905
+ "learning_rate": 8.248337028824834e-05,
1906
+ "loss": 0.8098,
1907
+ "step": 271
1908
+ },
1909
+ {
1910
+ "epoch": 1.791208791208791,
1911
+ "grad_norm": 0.48066723346710205,
1912
+ "learning_rate": 8.2039911308204e-05,
1913
+ "loss": 0.8288,
1914
+ "step": 272
1915
+ },
1916
+ {
1917
+ "epoch": 1.7978021978021979,
1918
+ "grad_norm": 0.564047634601593,
1919
+ "learning_rate": 8.159645232815965e-05,
1920
+ "loss": 0.9512,
1921
+ "step": 273
1922
+ },
1923
+ {
1924
+ "epoch": 1.8043956043956044,
1925
+ "grad_norm": 0.4820556938648224,
1926
+ "learning_rate": 8.11529933481153e-05,
1927
+ "loss": 0.499,
1928
+ "step": 274
1929
+ },
1930
+ {
1931
+ "epoch": 1.810989010989011,
1932
+ "grad_norm": 0.5948233604431152,
1933
+ "learning_rate": 8.070953436807095e-05,
1934
+ "loss": 0.8845,
1935
+ "step": 275
1936
+ },
1937
+ {
1938
+ "epoch": 1.8175824175824176,
1939
+ "grad_norm": 0.510066032409668,
1940
+ "learning_rate": 8.026607538802661e-05,
1941
+ "loss": 0.8913,
1942
+ "step": 276
1943
+ },
1944
+ {
1945
+ "epoch": 1.8241758241758241,
1946
+ "grad_norm": 0.5342652797698975,
1947
+ "learning_rate": 7.982261640798227e-05,
1948
+ "loss": 0.8842,
1949
+ "step": 277
1950
+ },
1951
+ {
1952
+ "epoch": 1.830769230769231,
1953
+ "grad_norm": 0.5228323340415955,
1954
+ "learning_rate": 7.937915742793793e-05,
1955
+ "loss": 0.8055,
1956
+ "step": 278
1957
+ },
1958
+ {
1959
+ "epoch": 1.8373626373626375,
1960
+ "grad_norm": 0.501943826675415,
1961
+ "learning_rate": 7.893569844789357e-05,
1962
+ "loss": 0.8469,
1963
+ "step": 279
1964
+ },
1965
+ {
1966
+ "epoch": 1.843956043956044,
1967
+ "grad_norm": 0.5378738641738892,
1968
+ "learning_rate": 7.849223946784923e-05,
1969
+ "loss": 0.9278,
1970
+ "step": 280
1971
+ },
1972
+ {
1973
+ "epoch": 1.8505494505494506,
1974
+ "grad_norm": 0.632314920425415,
1975
+ "learning_rate": 7.804878048780489e-05,
1976
+ "loss": 1.0605,
1977
+ "step": 281
1978
+ },
1979
+ {
1980
+ "epoch": 1.8571428571428572,
1981
+ "grad_norm": 0.40868574380874634,
1982
+ "learning_rate": 7.760532150776053e-05,
1983
+ "loss": 0.8974,
1984
+ "step": 282
1985
+ },
1986
+ {
1987
+ "epoch": 1.8637362637362638,
1988
+ "grad_norm": 0.5296427607536316,
1989
+ "learning_rate": 7.716186252771619e-05,
1990
+ "loss": 0.8518,
1991
+ "step": 283
1992
+ },
1993
+ {
1994
+ "epoch": 1.8703296703296703,
1995
+ "grad_norm": 0.48775559663772583,
1996
+ "learning_rate": 7.671840354767185e-05,
1997
+ "loss": 0.6894,
1998
+ "step": 284
1999
+ },
2000
+ {
2001
+ "epoch": 1.876923076923077,
2002
+ "grad_norm": 0.5466031432151794,
2003
+ "learning_rate": 7.627494456762749e-05,
2004
+ "loss": 0.847,
2005
+ "step": 285
2006
+ },
2007
+ {
2008
+ "epoch": 1.8835164835164835,
2009
+ "grad_norm": 0.6754628419876099,
2010
+ "learning_rate": 7.583148558758315e-05,
2011
+ "loss": 0.9727,
2012
+ "step": 286
2013
+ },
2014
+ {
2015
+ "epoch": 1.89010989010989,
2016
+ "grad_norm": 0.5291099548339844,
2017
+ "learning_rate": 7.538802660753881e-05,
2018
+ "loss": 0.9499,
2019
+ "step": 287
2020
+ },
2021
+ {
2022
+ "epoch": 1.8967032967032966,
2023
+ "grad_norm": 0.49350351095199585,
2024
+ "learning_rate": 7.494456762749445e-05,
2025
+ "loss": 0.6847,
2026
+ "step": 288
2027
+ },
2028
+ {
2029
+ "epoch": 1.9032967032967032,
2030
+ "grad_norm": 0.4854298233985901,
2031
+ "learning_rate": 7.450110864745011e-05,
2032
+ "loss": 0.8089,
2033
+ "step": 289
2034
+ },
2035
+ {
2036
+ "epoch": 1.9098901098901098,
2037
+ "grad_norm": 0.5256028771400452,
2038
+ "learning_rate": 7.405764966740577e-05,
2039
+ "loss": 0.789,
2040
+ "step": 290
2041
+ },
2042
+ {
2043
+ "epoch": 1.9164835164835163,
2044
+ "grad_norm": 0.5372645854949951,
2045
+ "learning_rate": 7.361419068736141e-05,
2046
+ "loss": 0.9326,
2047
+ "step": 291
2048
+ },
2049
+ {
2050
+ "epoch": 1.9230769230769231,
2051
+ "grad_norm": 0.4498584270477295,
2052
+ "learning_rate": 7.317073170731707e-05,
2053
+ "loss": 0.7562,
2054
+ "step": 292
2055
+ },
2056
+ {
2057
+ "epoch": 1.9296703296703297,
2058
+ "grad_norm": 0.5483140349388123,
2059
+ "learning_rate": 7.272727272727273e-05,
2060
+ "loss": 0.6764,
2061
+ "step": 293
2062
+ },
2063
+ {
2064
+ "epoch": 1.9362637362637363,
2065
+ "grad_norm": 0.6889297366142273,
2066
+ "learning_rate": 7.228381374722837e-05,
2067
+ "loss": 0.9722,
2068
+ "step": 294
2069
+ },
2070
+ {
2071
+ "epoch": 1.9428571428571428,
2072
+ "grad_norm": 0.4986286163330078,
2073
+ "learning_rate": 7.184035476718403e-05,
2074
+ "loss": 0.9781,
2075
+ "step": 295
2076
+ },
2077
+ {
2078
+ "epoch": 1.9494505494505494,
2079
+ "grad_norm": 0.6074146032333374,
2080
+ "learning_rate": 7.139689578713969e-05,
2081
+ "loss": 0.7487,
2082
+ "step": 296
2083
+ },
2084
+ {
2085
+ "epoch": 1.9560439560439562,
2086
+ "grad_norm": 0.5098879337310791,
2087
+ "learning_rate": 7.095343680709535e-05,
2088
+ "loss": 0.97,
2089
+ "step": 297
2090
+ },
2091
+ {
2092
+ "epoch": 1.9626373626373628,
2093
+ "grad_norm": 0.5738970041275024,
2094
+ "learning_rate": 7.0509977827051e-05,
2095
+ "loss": 0.7691,
2096
+ "step": 298
2097
+ },
2098
+ {
2099
+ "epoch": 1.9692307692307693,
2100
+ "grad_norm": 0.4587015211582184,
2101
+ "learning_rate": 7.006651884700666e-05,
2102
+ "loss": 0.7854,
2103
+ "step": 299
2104
+ },
2105
+ {
2106
+ "epoch": 1.975824175824176,
2107
+ "grad_norm": 0.5862131118774414,
2108
+ "learning_rate": 6.962305986696232e-05,
2109
+ "loss": 0.8636,
2110
+ "step": 300
2111
+ }
2112
+ ],
2113
+ "logging_steps": 1,
2114
+ "max_steps": 456,
2115
+ "num_input_tokens_seen": 0,
2116
+ "num_train_epochs": 3,
2117
+ "save_steps": 15,
2118
+ "stateful_callbacks": {
2119
+ "TrainerControl": {
2120
+ "args": {
2121
+ "should_epoch_stop": false,
2122
+ "should_evaluate": false,
2123
+ "should_log": false,
2124
+ "should_save": true,
2125
+ "should_training_stop": false
2126
+ },
2127
+ "attributes": {}
2128
+ }
2129
+ },
2130
+ "total_flos": 4.93298661433344e+16,
2131
+ "train_batch_size": 22,
2132
+ "trial_name": null,
2133
+ "trial_params": null
2134
+ }
checkpoint-300/training_args.bin ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a5771e71948dbda34583aadd9b95aaa5dcfa1508ab9cc504a7b946d80e194ff1
3
+ size 6417
checkpoint-300/vocab.json ADDED
The diff for this file is too large to render. See raw diff