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--- |
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library_name: transformers |
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base_model: zera09/custom-longt5-with-ts |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: segment_mask_token_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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# segment_mask_token_v2 |
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This model is a fine-tuned version of [zera09/custom-longt5-with-ts](https://huggingface.co/zera09/custom-longt5-with-ts) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0718 |
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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: 2e-05 |
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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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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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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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| No log | 1.0 | 72 | 5.8637 | |
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| 21.3135 | 2.0 | 144 | 1.6856 | |
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| 1.3759 | 3.0 | 216 | 1.0404 | |
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| 1.3759 | 4.0 | 288 | 0.6246 | |
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| 0.6906 | 5.0 | 360 | 0.3509 | |
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| 0.3575 | 6.0 | 432 | 0.2973 | |
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| 0.3583 | 7.0 | 504 | 0.1697 | |
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| 0.3583 | 8.0 | 576 | 0.1578 | |
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| 0.2914 | 9.0 | 648 | 0.1353 | |
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| 0.1716 | 10.0 | 720 | 0.1145 | |
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| 0.1716 | 11.0 | 792 | 0.0990 | |
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| 0.2055 | 12.0 | 864 | 0.0975 | |
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| 0.1352 | 13.0 | 936 | 0.0818 | |
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| 0.116 | 14.0 | 1008 | 0.0789 | |
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| 0.116 | 15.0 | 1080 | 0.0812 | |
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| 0.1264 | 16.0 | 1152 | 0.0800 | |
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| 0.1599 | 17.0 | 1224 | 0.0762 | |
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| 0.1599 | 18.0 | 1296 | 0.0720 | |
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| 0.0694 | 19.0 | 1368 | 0.0726 | |
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| 0.0742 | 20.0 | 1440 | 0.0718 | |
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### Framework versions |
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- Transformers 4.47.1 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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