End of training

README.md

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+---
+library_name: transformers
+license: apache-2.0
+base_model: albert/albert-xxlarge-v2
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: 27afceb9392c23d1674a5a2901ca7d34
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# 27afceb9392c23d1674a5a2901ca7d34
+
+This model is a fine-tuned version of [albert/albert-xxlarge-v2](https://huggingface.co/albert/albert-xxlarge-v2) on the dair-ai/emotion [split] dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3531
+- Data Size: 1.0
+- Epoch Runtime: 41.1003
+- Accuracy: 0.9088
+- F1 Macro: 0.8659
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 32
+- total_eval_batch_size: 32
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: constant
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
+| No log        | 0     | 0    | 2.2406          | 0         | 1.9154        | 0.0938   | 0.0641   |
+| No log        | 1     | 500  | 1.7164          | 0.0078    | 2.2981        | 0.2359   | 0.1245   |
+| No log        | 2     | 1000 | 1.7238          | 0.0156    | 2.6170        | 0.2747   | 0.1135   |
+| No log        | 3     | 1500 | 1.5864          | 0.0312    | 3.4158        | 0.3508   | 0.0944   |
+| No log        | 4     | 2000 | 1.5906          | 0.0625    | 4.7034        | 0.3054   | 0.1008   |
+| 0.0883        | 5     | 2500 | 1.4474          | 0.125     | 7.0518        | 0.5050   | 0.2052   |
+| 1.3713        | 6     | 3000 | 1.3480          | 0.25      | 12.0165       | 0.5469   | 0.2198   |
+| 0.1954        | 7     | 3500 | 1.0987          | 0.5       | 21.9685       | 0.6144   | 0.2500   |
+| 0.4637        | 8.0   | 4000 | 0.4034          | 1.0       | 41.8969       | 0.8831   | 0.7363   |
+| 0.4674        | 9.0   | 4500 | 0.4547          | 1.0       | 41.4539       | 0.8866   | 0.7876   |
+| 0.3519        | 10.0  | 5000 | 0.3257          | 1.0       | 41.3873       | 0.9057   | 0.8543   |
+| 0.2821        | 11.0  | 5500 | 0.2998          | 1.0       | 41.3973       | 0.9113   | 0.8625   |
+| 0.2597        | 12.0  | 6000 | 0.2644          | 1.0       | 41.4418       | 0.9148   | 0.8722   |
+| 0.2649        | 13.0  | 6500 | 0.3314          | 1.0       | 41.2494       | 0.9158   | 0.8698   |
+| 0.255         | 14.0  | 7000 | 0.2704          | 1.0       | 41.4583       | 0.9113   | 0.8641   |
+| 0.1864        | 15.0  | 7500 | 0.3561          | 1.0       | 41.3138       | 0.9178   | 0.8721   |
+| 0.2955        | 16.0  | 8000 | 0.3531          | 1.0       | 41.1003       | 0.9088   | 0.8659   |
+
+
+### Framework versions
+
+- Transformers 4.57.0
+- Pytorch 2.8.0+cu128
+- Datasets 4.3.0
+- Tokenizers 0.22.1

config.json

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+{
+  "architectures": [
+    "AlbertForSequenceClassification"
+  ],
+  "attention_probs_dropout_prob": 0,
+  "bos_token_id": 2,
+  "classifier_dropout_prob": 0.1,
+  "down_scale_factor": 1,
+  "dtype": "float32",
+  "embedding_size": 128,
+  "eos_token_id": 3,
+  "gap_size": 0,
+  "hidden_act": "gelu_new",
+  "hidden_dropout_prob": 0,
+  "hidden_size": 4096,
+  "id2label": {
+    "0": "LABEL_0",
+    "1": "LABEL_1",
+    "2": "LABEL_2",
+    "3": "LABEL_3",
+    "4": "LABEL_4",
+    "5": "LABEL_5"
+  },
+  "initializer_range": 0.02,
+  "inner_group_num": 1,
+  "intermediate_size": 16384,
+  "label2id": {
+    "LABEL_0": 0,
+    "LABEL_1": 1,
+    "LABEL_2": 2,
+    "LABEL_3": 3,
+    "LABEL_4": 4,
+    "LABEL_5": 5
+  },
+  "layer_norm_eps": 1e-12,
+  "layers_to_keep": [],
+  "max_position_embeddings": 512,
+  "model_type": "albert",
+  "net_structure_type": 0,
+  "num_attention_heads": 64,
+  "num_hidden_groups": 1,
+  "num_hidden_layers": 12,
+  "num_memory_blocks": 0,
+  "pad_token_id": 0,
+  "position_embedding_type": "absolute",
+  "problem_type": "single_label_classification",
+  "transformers_version": "4.57.0",
+  "type_vocab_size": 2,
+  "vocab_size": 30000
+}

model.safetensors

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special_tokens_map.json

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+{
+  "bos_token": "[CLS]",
+  "cls_token": "[CLS]",
+  "eos_token": "[SEP]",
+  "mask_token": {
+    "content": "[MASK]",
+    "lstrip": true,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": "<pad>",
+  "sep_token": "[SEP]",
+  "unk_token": "<unk>"
+}

spiece.model

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+size 760289

tokenizer_config.json

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+{
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
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+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": true,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "[CLS]",
+  "clean_up_tokenization_spaces": false,
+  "cls_token": "[CLS]",
+  "do_lower_case": true,
+  "eos_token": "[SEP]",
+  "extra_special_tokens": {},
+  "keep_accents": false,
+  "mask_token": "[MASK]",
+  "model_max_length": 512,
+  "pad_token": "<pad>",
+  "remove_space": true,
+  "sep_token": "[SEP]",
+  "tokenizer_class": "AlbertTokenizer",
+  "unk_token": "<unk>"
+}

training_args.bin

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