---
library_name: peft
license: other
base_model: Qwen/Qwen2.5-3B-Instruct
tags:
- axolotl
- generated_from_trainer
model-index:
- name: 702609de-5f88-479b-8c42-393d171935f2
  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. -->

[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.1`
```yaml
adapter: lora
base_model: Qwen/Qwen2.5-3B-Instruct
bf16: auto
dataset_prepared_path: null
datasets:
- data_files:
  - a9370d8bc6e0e8be_train_data.json
  ds_type: json
  format: custom
  path: /root/G.O.D-test/core/data/a9370d8bc6e0e8be_train_data.json
  type:
    field_input: Complex_CoT
    field_instruction: Question
    field_output: Response
    format: '{instruction} {input}'
    no_input_format: '{instruction}'
    system_format: '{system}'
    system_prompt: ''
debug: null
deepspeed: null
early_stopping_patience: null
eval_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 10
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: false
group_by_length: false
hub_model_id: souging/702609de-5f88-479b-8c42-393d171935f2
hub_repo: null
hub_strategy: checkpoint
hub_token: null
learning_rate: 0.0002
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 32
lora_dropout: 0.05
lora_fan_in_fan_out: null
lora_model_dir: null
lora_r: 16
lora_target_linear: true
lr_scheduler: cosine
max_steps: 500
micro_batch_size: 4
mlflow_experiment_name: /tmp/a9370d8bc6e0e8be_train_data.json
model_type: AutoModelForCausalLM
num_epochs: 4
optimizer: adamw_bnb_8bit
output_dir: miner_id_24
pad_to_sequence_len: true
resume_from_checkpoint: null
s2_attention: null
sample_packing: false
saves_per_epoch: 10
sequence_len: 1024
strict: false
tf32: false
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
val_set_size: 0.05
wandb_entity: null
wandb_mode: online
wandb_name: 9d95b060-41cc-4d8a-b03d-190792edce50
wandb_project: Gradients-On-Demand
wandb_run: your_name
wandb_runid: 9d95b060-41cc-4d8a-b03d-190792edce50
warmup_steps: 100
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# 702609de-5f88-479b-8c42-393d171935f2

This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7429

## 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: 0.0002
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 500

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0533        | 0.0055 | 1    | 1.2178          |
| 1.1372        | 0.0712 | 13   | 1.1764          |
| 0.9056        | 0.1425 | 26   | 0.8935          |
| 0.7864        | 0.2137 | 39   | 0.8048          |
| 0.796         | 0.2849 | 52   | 0.7839          |
| 0.7511        | 0.3562 | 65   | 0.7741          |
| 0.7576        | 0.4274 | 78   | 0.7689          |
| 0.7403        | 0.4986 | 91   | 0.7618          |
| 0.7916        | 0.5699 | 104  | 0.7577          |
| 0.7765        | 0.6411 | 117  | 0.7547          |
| 0.7039        | 0.7123 | 130  | 0.7529          |
| 0.7594        | 0.7836 | 143  | 0.7501          |
| 0.7966        | 0.8548 | 156  | 0.7477          |
| 0.8105        | 0.9260 | 169  | 0.7468          |
| 0.6799        | 0.9973 | 182  | 0.7456          |
| 0.7117        | 1.0685 | 195  | 0.7446          |
| 0.7082        | 1.1397 | 208  | 0.7479          |
| 0.7889        | 1.2110 | 221  | 0.7464          |
| 0.6094        | 1.2822 | 234  | 0.7451          |
| 0.7105        | 1.3534 | 247  | 0.7445          |
| 0.7257        | 1.4247 | 260  | 0.7432          |
| 0.7152        | 1.4959 | 273  | 0.7416          |
| 0.7657        | 1.5671 | 286  | 0.7402          |
| 0.7808        | 1.6384 | 299  | 0.7396          |
| 0.7059        | 1.7096 | 312  | 0.7394          |
| 0.7537        | 1.7808 | 325  | 0.7377          |
| 0.6318        | 1.8521 | 338  | 0.7373          |
| 0.7712        | 1.9233 | 351  | 0.7369          |
| 0.7703        | 1.9945 | 364  | 0.7362          |
| 0.6556        | 2.0658 | 377  | 0.7415          |
| 0.6248        | 2.1370 | 390  | 0.7405          |
| 0.6789        | 2.2082 | 403  | 0.7426          |
| 0.6595        | 2.2795 | 416  | 0.7436          |
| 0.6761        | 2.3507 | 429  | 0.7431          |
| 0.6399        | 2.4219 | 442  | 0.7434          |
| 0.6672        | 2.4932 | 455  | 0.7434          |
| 0.5704        | 2.5644 | 468  | 0.7433          |
| 0.6552        | 2.6356 | 481  | 0.7429          |
| 0.6455        | 2.7068 | 494  | 0.7429          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.1
- Tokenizers 0.20.3