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--- |
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license: apache-2.0 |
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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: bigscience/mt0-base |
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model-index: |
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- name: mt0-base_IA3_lr5e-05_bs4_epoch20_wd0.01 |
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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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# mt0-base_IA3_lr5e-05_bs4_epoch20_wd0.01 |
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This model is a fine-tuned version of [bigscience/mt0-base](https://huggingface.co/bigscience/mt0-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0587 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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_steps: 500 |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.5794 | 1.0 | 157 | 0.3078 | |
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| 0.5388 | 2.0 | 314 | 0.2805 | |
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| 0.5028 | 3.0 | 471 | 0.2418 | |
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| 0.4281 | 4.0 | 628 | 0.2026 | |
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| 0.3694 | 5.0 | 785 | 0.1730 | |
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| 0.3233 | 6.0 | 942 | 0.1490 | |
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| 0.295 | 7.0 | 1099 | 0.1303 | |
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| 0.2743 | 8.0 | 1256 | 0.1150 | |
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| 0.2312 | 9.0 | 1413 | 0.1027 | |
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| 0.2173 | 10.0 | 1570 | 0.0931 | |
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| 0.1977 | 11.0 | 1727 | 0.0853 | |
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| 0.189 | 12.0 | 1884 | 0.0790 | |
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| 0.1668 | 13.0 | 2041 | 0.0738 | |
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| 0.1703 | 14.0 | 2198 | 0.0695 | |
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| 0.1624 | 15.0 | 2355 | 0.0660 | |
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| 0.1532 | 16.0 | 2512 | 0.0632 | |
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| 0.1448 | 17.0 | 2669 | 0.0612 | |
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| 0.1487 | 18.0 | 2826 | 0.0598 | |
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| 0.1517 | 19.0 | 2983 | 0.0590 | |
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| 0.1418 | 20.0 | 3140 | 0.0587 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.36.2 |
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- Pytorch 2.0.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
