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| base_model: shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat | |
| library_name: peft | |
| license: other | |
| tags: | |
| - llama-factory | |
| - lora | |
| - generated_from_trainer | |
| model-index: | |
| - name: Mistral-7B-v0.3-Chinese-Chat | |
| 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. --> | |
| # Mistral-7B-v0.3-Chinese-Chat | |
| This model is a fine-tuned version of [shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat](https://huggingface.co/shenzhi-wang/Mistral-7B-v0.3-Chinese-Chat) on the alpaca_mgtv_p2 dataset. | |
| It achieves the following results on the evaluation set: | |
| - Loss: 0.1295 | |
| ## 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: 0.0001 | |
| - train_batch_size: 16 | |
| - eval_batch_size: 1 | |
| - seed: 42 | |
| - gradient_accumulation_steps: 8 | |
| - total_train_batch_size: 128 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: cosine | |
| - lr_scheduler_warmup_ratio: 0.1 | |
| - num_epochs: 2.0 | |
| ### Training results | |
| | Training Loss | Epoch | Step | Validation Loss | | |
| |:-------------:|:------:|:----:|:---------------:| | |
| | 0.1803 | 0.1990 | 35 | 0.1682 | | |
| | 0.1583 | 0.3980 | 70 | 0.1548 | | |
| | 0.1439 | 0.5970 | 105 | 0.1490 | | |
| | 0.1488 | 0.7960 | 140 | 0.1356 | | |
| | 0.1385 | 0.9950 | 175 | 0.1367 | | |
| | 0.1092 | 1.1940 | 210 | 0.1316 | | |
| | 0.1282 | 1.3930 | 245 | 0.1276 | | |
| | 0.1135 | 1.5920 | 280 | 0.1306 | | |
| | 0.1071 | 1.7910 | 315 | 0.1307 | | |
| | 0.1075 | 1.9900 | 350 | 0.1295 | | |
| ### Framework versions | |
| - PEFT 0.11.1 | |
| - Transformers 4.43.3 | |
| - Pytorch 2.4.0+cu121 | |
| - Datasets 2.19.1 | |
| - Tokenizers 0.19.1 |