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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: results |
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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/tarunwandb/huggingface/runs/5mqa1xeb) |
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# results |
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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 the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2406 |
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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: 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: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.2518 | 0.0530 | 100 | 1.3453 | |
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| 1.3137 | 0.1059 | 200 | 1.2820 | |
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| 1.2681 | 0.1589 | 300 | 1.2684 | |
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| 1.2611 | 0.2118 | 400 | 1.2625 | |
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| 1.2599 | 0.2648 | 500 | 1.2587 | |
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| 1.2709 | 0.3177 | 600 | 1.2561 | |
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| 1.2607 | 0.3707 | 700 | 1.2537 | |
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| 1.2502 | 0.4236 | 800 | 1.2515 | |
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| 1.2475 | 0.4766 | 900 | 1.2494 | |
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| 1.2479 | 0.5295 | 1000 | 1.2476 | |
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| 1.2535 | 0.5825 | 1100 | 1.2469 | |
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| 1.2546 | 0.6354 | 1200 | 1.2455 | |
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| 1.2498 | 0.6884 | 1300 | 1.2440 | |
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| 1.2445 | 0.7413 | 1400 | 1.2433 | |
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| 1.247 | 0.7943 | 1500 | 1.2423 | |
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| 1.2438 | 0.8472 | 1600 | 1.2418 | |
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| 1.2434 | 0.9002 | 1700 | 1.2413 | |
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| 1.2425 | 0.9531 | 1800 | 1.2406 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
