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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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base_model: microsoft/Phi-3-mini-4k-instruct |
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model-index: |
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- name: phi-3-mini-QLoRA |
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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-QLoRA |
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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: 0.5741 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_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: 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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| 1.1422 | 0.1810 | 100 | 0.6625 | |
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| 0.6238 | 0.3619 | 200 | 0.6002 | |
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| 0.5932 | 0.5429 | 300 | 0.5906 | |
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| 0.5926 | 0.7238 | 400 | 0.5860 | |
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| 0.5794 | 0.9048 | 500 | 0.5834 | |
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| 0.5868 | 1.0857 | 600 | 0.5815 | |
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| 0.5711 | 1.2667 | 700 | 0.5796 | |
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| 0.5729 | 1.4476 | 800 | 0.5785 | |
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| 0.5858 | 1.6286 | 900 | 0.5772 | |
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| 0.5732 | 1.8095 | 1000 | 0.5763 | |
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| 0.5736 | 1.9905 | 1100 | 0.5756 | |
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| 0.5638 | 2.1715 | 1200 | 0.5754 | |
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| 0.5769 | 2.3524 | 1300 | 0.5746 | |
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| 0.5668 | 2.5334 | 1400 | 0.5745 | |
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| 0.5675 | 2.7143 | 1500 | 0.5742 | |
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| 0.5693 | 2.8953 | 1600 | 0.5741 | |
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### Framework versions |
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- PEFT 0.10.0 |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
