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--- |
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library_name: transformers |
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license: other |
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base_model: saves/Yi-1.5-9B-pt-241124 |
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tags: |
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- llama-factory |
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- full |
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- generated_from_trainer |
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model-index: |
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- name: Yi-1.5-9B-sft-241128 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# Yi-1.5-9B-sft-241128 |
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This model is a fine-tuned version of [saves/Yi-1.5-9B-pt-241124](https://huggingface.co/saves/Yi-1.5-9B-pt-241124) on the chinese-medical-dialogue, the CMB, the cMedQA2, the CMExam, the CMtMedQA, the COIG-CQIA-full, the COIG_full, the HuatuoGPT_sft_data_v, the huatuo_encyclopedia_q, the huatuo_lite, the imcs21, the Med-single-choice, the Medical_dialogue_system_en_single_turn, the qizhengpt-sft-20, the self_cognition, the sharegpt_zh_38K_format, the shennong, the shibing642-medica, the tigerbot_sft_data, the xywy-KG and the zhongyi-zhiku datasets. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.4478 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2.5e-06 |
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- train_batch_size: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- total_train_batch_size: 32 |
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- total_eval_batch_size: 32 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.05 |
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- num_epochs: 2.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 1.6544 | 0.1277 | 1000 | 1.6105 | |
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| 1.5595 | 0.2554 | 2000 | 1.5668 | |
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| 1.5297 | 0.3830 | 3000 | 1.5394 | |
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| 1.5637 | 0.5107 | 4000 | 1.5188 | |
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| 1.5051 | 0.6384 | 5000 | 1.5028 | |
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| 1.4765 | 0.7661 | 6000 | 1.4895 | |
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| 1.4504 | 0.8938 | 7000 | 1.4779 | |
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| 1.4084 | 1.0215 | 8000 | 1.4716 | |
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| 1.4292 | 1.1491 | 9000 | 1.4653 | |
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| 1.4349 | 1.2768 | 10000 | 1.4597 | |
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| 1.4442 | 1.4045 | 11000 | 1.4548 | |
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| 1.422 | 1.5322 | 12000 | 1.4517 | |
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| 1.3986 | 1.6599 | 13000 | 1.4491 | |
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| 1.3949 | 1.7875 | 14000 | 1.4482 | |
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| 1.4241 | 1.9152 | 15000 | 1.4478 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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