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--- |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: longt5_xl_sfd_bp_40 |
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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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# longt5_xl_sfd_bp_40 |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.6048 |
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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: 0.001 |
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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: 32 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: constant |
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- num_epochs: 25.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.1855 | 0.97 | 14 | 2.5320 | |
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| 0.1635 | 1.95 | 28 | 2.4299 | |
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| 0.1272 | 2.99 | 43 | 2.9443 | |
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| 0.1113 | 3.97 | 57 | 2.8813 | |
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| 0.0819 | 4.94 | 71 | 3.0005 | |
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| 0.0782 | 5.98 | 86 | 3.0224 | |
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| 0.0588 | 6.96 | 100 | 3.1903 | |
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| 0.0729 | 8.0 | 115 | 2.5871 | |
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| 0.0473 | 8.97 | 129 | 3.2830 | |
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| 0.113 | 9.95 | 143 | 3.3443 | |
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| 0.0364 | 10.99 | 158 | 3.3243 | |
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| 0.0321 | 11.97 | 172 | 3.3962 | |
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| 0.0302 | 12.94 | 186 | 3.4508 | |
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| 0.0717 | 13.98 | 201 | 3.4166 | |
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| 0.0746 | 14.96 | 215 | 2.8975 | |
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| 0.0548 | 16.0 | 230 | 3.0853 | |
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| 0.0507 | 16.97 | 244 | 3.0706 | |
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| 0.0442 | 17.95 | 258 | 3.2759 | |
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| 0.0396 | 18.99 | 273 | 3.1962 | |
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| 0.0351 | 19.97 | 287 | 3.3108 | |
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| 0.0306 | 20.94 | 301 | 3.2607 | |
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| 0.0267 | 21.98 | 316 | 3.4015 | |
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| 0.1454 | 22.96 | 330 | 2.6912 | |
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| 0.0252 | 24.0 | 345 | 3.4576 | |
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| 0.0187 | 24.35 | 350 | 3.6048 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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