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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: phi3-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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# phi3-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: 0.5538 |
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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: 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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| 0.8693 | 0.1809 | 100 | 0.6163 | |
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| 0.5925 | 0.3618 | 200 | 0.5740 | |
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| 0.5675 | 0.5427 | 300 | 0.5667 | |
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| 0.571 | 0.7237 | 400 | 0.5631 | |
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| 0.555 | 0.9046 | 500 | 0.5613 | |
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| 0.566 | 1.0855 | 600 | 0.5597 | |
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| 0.5502 | 1.2664 | 700 | 0.5583 | |
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| 0.5524 | 1.4473 | 800 | 0.5575 | |
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| 0.5653 | 1.6282 | 900 | 0.5565 | |
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| 0.5515 | 1.8091 | 1000 | 0.5561 | |
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| 0.5523 | 1.9900 | 1100 | 0.5555 | |
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| 0.5422 | 2.1710 | 1200 | 0.5555 | |
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| 0.559 | 2.3519 | 1300 | 0.5546 | |
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| 0.5466 | 2.5328 | 1400 | 0.5542 | |
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| 0.5476 | 2.7137 | 1500 | 0.5541 | |
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| 0.55 | 2.8946 | 1600 | 0.5538 | |
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### Framework versions |
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- PEFT 0.13.0 |
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- Transformers 4.45.1 |
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- Pytorch 2.2.2 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
