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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-v3-smallsubset |
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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-v3-smallsubset |
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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: 1.4985 |
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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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| No log | 0.99 | 31 | 1.2173 | |
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| No log | 1.98 | 62 | 1.1653 | |
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| No log | 2.98 | 93 | 1.1535 | |
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| No log | 4.0 | 125 | 1.1498 | |
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| No log | 4.99 | 156 | 1.1562 | |
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| No log | 5.98 | 187 | 1.1682 | |
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| 1.0347 | 6.98 | 218 | 1.1832 | |
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| 1.0347 | 8.0 | 250 | 1.1934 | |
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| 1.0347 | 8.99 | 281 | 1.2183 | |
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| 1.0347 | 9.98 | 312 | 1.2468 | |
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| 1.0347 | 10.98 | 343 | 1.2760 | |
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| 1.0347 | 12.0 | 375 | 1.3096 | |
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| 0.7791 | 12.99 | 406 | 1.3348 | |
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| 0.7791 | 13.98 | 437 | 1.3695 | |
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| 0.7791 | 14.98 | 468 | 1.3935 | |
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| 0.7791 | 16.0 | 500 | 1.4104 | |
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| 0.7791 | 16.99 | 531 | 1.4235 | |
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| 0.7791 | 17.98 | 562 | 1.4546 | |
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| 0.7791 | 18.98 | 593 | 1.4709 | |
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| 0.5995 | 20.0 | 625 | 1.4790 | |
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| 0.5995 | 20.99 | 656 | 1.4889 | |
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| 0.5995 | 21.98 | 687 | 1.4942 | |
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| 0.5995 | 22.98 | 718 | 1.4954 | |
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| 0.5995 | 24.0 | 750 | 1.4982 | |
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| 0.5995 | 24.8 | 775 | 1.4985 | |
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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 |
