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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 |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/esawtooth-rohit-jain/learning/runs/9hs3unns) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/esawtooth-rohit-jain/learning/runs/3vivu1t4) |
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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/esawtooth-rohit-jain/learning/runs/qnf9h94c) |
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# phi-3-mini-LoRA |
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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: 0.5586 |
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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: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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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| 0.7527 | 0.1131 | 250 | 0.6002 | |
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| 0.5924 | 0.2262 | 500 | 0.5809 | |
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| 0.5811 | 0.3393 | 750 | 0.5759 | |
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| 0.5827 | 0.4524 | 1000 | 0.5717 | |
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| 0.5767 | 0.5655 | 1250 | 0.5704 | |
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| 0.5711 | 0.6787 | 1500 | 0.5678 | |
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| 0.5691 | 0.7918 | 1750 | 0.5672 | |
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| 0.5635 | 0.9049 | 2000 | 0.5654 | |
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| 0.5712 | 1.0180 | 2250 | 0.5650 | |
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| 0.5611 | 1.1311 | 2500 | 0.5647 | |
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| 0.555 | 1.2442 | 2750 | 0.5631 | |
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| 0.5505 | 1.3573 | 3000 | 0.5628 | |
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| 0.5657 | 1.4704 | 3250 | 0.5624 | |
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| 0.563 | 1.5835 | 3500 | 0.5617 | |
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| 0.5577 | 1.6966 | 3750 | 0.5614 | |
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| 0.5578 | 1.8098 | 4000 | 0.5603 | |
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| 0.5552 | 1.9229 | 4250 | 0.5604 | |
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| 0.5514 | 2.0360 | 4500 | 0.5600 | |
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| 0.5473 | 2.1491 | 4750 | 0.5603 | |
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| 0.5573 | 2.2622 | 5000 | 0.5596 | |
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| 0.5423 | 2.3753 | 5250 | 0.5599 | |
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| 0.5579 | 2.4884 | 5500 | 0.5595 | |
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| 0.5403 | 2.6015 | 5750 | 0.5591 | |
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| 0.5475 | 2.7146 | 6000 | 0.5593 | |
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| 0.5477 | 2.8277 | 6250 | 0.5590 | |
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| 0.5438 | 2.9408 | 6500 | 0.5586 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.43.1 |
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- Pytorch 2.4.0a0+3bcc3cddb5.nv24.07 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
