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--- |
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license: mit |
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library_name: peft |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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- health |
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- medical |
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base_model: microsoft/phi-2 |
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model-index: |
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- name: medical |
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results: [] |
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datasets: |
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- wangrongsheng/HealthCareMagic-100k-en |
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language: |
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- en |
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metrics: |
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- perplexity |
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- precision |
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- accuracy |
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- character |
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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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# medical |
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This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on an unknown dataset. |
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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: 0.0002 |
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- train_batch_size: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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: 0.03 |
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- training_steps: 500 |
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### Training results |
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### Framework versions |
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- PEFT 0.7.2.dev0 |
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- Transformers 4.37.1 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.1 |
