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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/dhanishetty-personaluse/huggingface/runs/q8sd8pe7) |
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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: 0.4578 |
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## Platform - *** Trained on Google Colab *** |
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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: 1e-05 |
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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: 2 |
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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: polynomial |
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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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| 0.9205 | 0.2022 | 100 | 0.9239 | |
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| 0.6297 | 0.4044 | 200 | 0.6279 | |
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| 0.4782 | 0.6067 | 300 | 0.5032 | |
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| 0.494 | 0.8089 | 400 | 0.4833 | |
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| 0.4613 | 1.0111 | 500 | 0.4755 | |
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| 0.4587 | 1.2133 | 600 | 0.4708 | |
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| 0.4643 | 1.4156 | 700 | 0.4673 | |
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| 0.4498 | 1.6178 | 800 | 0.4645 | |
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| 0.506 | 1.8200 | 900 | 0.4624 | |
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| 0.4235 | 2.0222 | 1000 | 0.4608 | |
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| 0.4798 | 2.2245 | 1100 | 0.4597 | |
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| 0.4646 | 2.4267 | 1200 | 0.4586 | |
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| 0.4636 | 2.6289 | 1300 | 0.4580 | |
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| 0.4596 | 2.8311 | 1400 | 0.4578 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.3 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
