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--- |
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base_model: microsoft/Phi-3-mini-4k-instruct |
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library_name: peft |
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license: mit |
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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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model-index: |
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- name: phi-3-mini-LoRA-MEDQA-Extended-V2 |
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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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# phi-3-mini-LoRA-MEDQA-Extended-V2 |
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This model is a fine-tuned version of [microsoft/Phi-3-mini-4k-instruct](https://huggingface.co/microsoft/Phi-3-mini-4k-instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6514 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.7812 | 0.2205 | 100 | 0.6947 | |
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| 0.6795 | 0.4410 | 200 | 0.6694 | |
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| 0.6686 | 0.6615 | 300 | 0.6633 | |
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| 0.662 | 0.8820 | 400 | 0.6597 | |
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| 0.6603 | 1.1025 | 500 | 0.6578 | |
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| 0.6586 | 1.3230 | 600 | 0.6566 | |
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| 0.6538 | 1.5436 | 700 | 0.6552 | |
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| 0.6551 | 1.7641 | 800 | 0.6539 | |
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| 0.6542 | 1.9846 | 900 | 0.6535 | |
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| 0.65 | 2.2051 | 1000 | 0.6525 | |
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| 0.6522 | 2.4256 | 1100 | 0.6519 | |
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| 0.6526 | 2.6461 | 1200 | 0.6515 | |
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| 0.6501 | 2.8666 | 1300 | 0.6514 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.43.3 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
