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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-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: 0.4084 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 1.415 | 1.1765 | 5 | 1.4148 | |
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| 1.2791 | 2.3529 | 10 | 1.2542 | |
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| 1.0303 | 3.5294 | 15 | 0.9828 | |
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| 0.7989 | 4.7059 | 20 | 0.7193 | |
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| 0.5792 | 5.8824 | 25 | 0.5793 | |
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| 0.5074 | 7.0588 | 30 | 0.5133 | |
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| 0.4558 | 8.2353 | 35 | 0.4714 | |
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| 0.361 | 9.4118 | 40 | 0.4478 | |
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| 0.3751 | 10.5882 | 45 | 0.4236 | |
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| 0.2908 | 11.7647 | 50 | 0.4106 | |
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| 0.263 | 12.9412 | 55 | 0.3855 | |
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| 0.2515 | 14.1176 | 60 | 0.3760 | |
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| 0.2391 | 15.2941 | 65 | 0.3752 | |
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| 0.1973 | 16.4706 | 70 | 0.3723 | |
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| 0.1638 | 17.6471 | 75 | 0.3740 | |
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| 0.1776 | 18.8235 | 80 | 0.3868 | |
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| 0.2008 | 20.0 | 85 | 0.3798 | |
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| 0.1569 | 21.1765 | 90 | 0.3848 | |
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| 0.1284 | 22.3529 | 95 | 0.3901 | |
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| 0.1171 | 23.5294 | 100 | 0.3969 | |
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| 0.1364 | 24.7059 | 105 | 0.3950 | |
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| 0.1401 | 25.8824 | 110 | 0.4070 | |
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| 0.1195 | 27.0588 | 115 | 0.4091 | |
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| 0.1219 | 28.2353 | 120 | 0.4084 | |
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### Framework versions |
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- PEFT 0.13.2 |
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- Transformers 4.45.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
