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--- |
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license: mit |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: microsoft/phi-1_5 |
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model-index: |
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- name: phi-1_5-finetuned-qlora-cluster-gsm8k-v2 |
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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-1_5-finetuned-qlora-cluster-gsm8k-v2 |
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This model is a fine-tuned version of [microsoft/phi-1_5](https://huggingface.co/microsoft/phi-1_5) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9003 |
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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: 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: cosine |
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- num_epochs: 25 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.0468 | 1.0 | 233 | 1.1314 | |
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| 0.9635 | 2.0 | 467 | 1.1069 | |
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| 0.9293 | 3.0 | 701 | 1.1129 | |
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| 0.8905 | 4.0 | 935 | 1.1269 | |
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| 0.8478 | 5.0 | 1168 | 1.1509 | |
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| 0.7686 | 6.0 | 1402 | 1.1727 | |
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| 0.7125 | 7.0 | 1636 | 1.2254 | |
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| 0.6637 | 8.0 | 1870 | 1.2571 | |
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| 0.6155 | 9.0 | 2103 | 1.3230 | |
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| 0.574 | 10.0 | 2337 | 1.3985 | |
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| 0.5273 | 11.0 | 2571 | 1.4532 | |
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| 0.451 | 12.0 | 2805 | 1.5160 | |
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| 0.4102 | 13.0 | 3038 | 1.5888 | |
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| 0.3802 | 14.0 | 3272 | 1.6469 | |
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| 0.3586 | 15.0 | 3506 | 1.6916 | |
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| 0.3391 | 16.0 | 3740 | 1.7576 | |
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| 0.3194 | 17.0 | 3973 | 1.7898 | |
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| 0.293 | 18.0 | 4207 | 1.8284 | |
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| 0.2815 | 19.0 | 4441 | 1.8460 | |
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| 0.2739 | 20.0 | 4675 | 1.8681 | |
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| 0.2693 | 21.0 | 4908 | 1.8821 | |
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| 0.2646 | 22.0 | 5142 | 1.8908 | |
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| 0.2614 | 23.0 | 5376 | 1.8954 | |
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| 0.2577 | 24.0 | 5610 | 1.8993 | |
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| 0.2566 | 24.92 | 5825 | 1.9003 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.37.2 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.15.1 |
