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--- |
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base_model: microsoft/Phi-3.5-mini-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 |
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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 |
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This model is a fine-tuned version of [microsoft/Phi-3.5-mini-instruct](https://huggingface.co/microsoft/Phi-3.5-mini-instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3840 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 3407 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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_steps: 5 |
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- training_steps: 120 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 1.5071 | 0.5882 | 5 | 1.4674 | |
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| 1.1659 | 1.1765 | 10 | 1.0849 | |
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| 0.894 | 1.7647 | 15 | 0.8655 | |
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| 0.7243 | 2.3529 | 20 | 0.6989 | |
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| 0.5752 | 2.9412 | 25 | 0.5856 | |
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| 0.5724 | 3.5294 | 30 | 0.5257 | |
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| 0.4834 | 4.1176 | 35 | 0.4875 | |
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| 0.3861 | 4.7059 | 40 | 0.4588 | |
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| 0.35 | 5.2941 | 45 | 0.4368 | |
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| 0.3126 | 5.8824 | 50 | 0.4251 | |
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| 0.367 | 6.4706 | 55 | 0.4080 | |
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| 0.2792 | 7.0588 | 60 | 0.3955 | |
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| 0.3952 | 7.6471 | 65 | 0.3914 | |
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| 0.2854 | 8.2353 | 70 | 0.3784 | |
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| 0.3224 | 8.8235 | 75 | 0.3867 | |
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| 0.3187 | 9.4118 | 80 | 0.3765 | |
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| 0.1675 | 10.0 | 85 | 0.3799 | |
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| 0.1888 | 10.5882 | 90 | 0.3858 | |
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| 0.2021 | 11.1765 | 95 | 0.3759 | |
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| 0.1518 | 11.7647 | 100 | 0.3868 | |
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| 0.2075 | 12.3529 | 105 | 0.3915 | |
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| 0.1497 | 12.9412 | 110 | 0.3814 | |
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| 0.1797 | 13.5294 | 115 | 0.3821 | |
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| 0.1606 | 14.1176 | 120 | 0.3840 | |
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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 2.4.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
