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--- |
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library_name: transformers |
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license: mit |
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base_model: mhr2004/roberta-large-nsp-1000000-1e-06-32 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: roberta-large-nsp-1000000-1e-06-32-negcommonsensebalanced-1e-06-64 |
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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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# roberta-large-nsp-1000000-1e-06-32-negcommonsensebalanced-1e-06-64 |
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This model is a fine-tuned version of [mhr2004/roberta-large-nsp-1000000-1e-06-32](https://huggingface.co/mhr2004/roberta-large-nsp-1000000-1e-06-32) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3364 |
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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: 1e-06 |
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- train_batch_size: 256 |
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- eval_batch_size: 1024 |
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- seed: 42 |
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- optimizer: Use 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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 0.5348 | 1.0 | 795 | 0.4701 | |
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| 0.4543 | 2.0 | 1590 | 0.4139 | |
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| 0.4173 | 3.0 | 2385 | 0.3899 | |
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| 0.3926 | 4.0 | 3180 | 0.3784 | |
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| 0.3702 | 5.0 | 3975 | 0.3663 | |
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| 0.3578 | 6.0 | 4770 | 0.3554 | |
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| 0.3472 | 7.0 | 5565 | 0.3466 | |
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| 0.3334 | 8.0 | 6360 | 0.3467 | |
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| 0.3206 | 9.0 | 7155 | 0.3425 | |
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| 0.3114 | 10.0 | 7950 | 0.3408 | |
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| 0.3033 | 11.0 | 8745 | 0.3340 | |
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| 0.2948 | 12.0 | 9540 | 0.3339 | |
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| 0.2858 | 13.0 | 10335 | 0.3385 | |
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| 0.2829 | 14.0 | 11130 | 0.3333 | |
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| 0.2775 | 15.0 | 11925 | 0.3334 | |
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| 0.2652 | 16.0 | 12720 | 0.3367 | |
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| 0.2645 | 17.0 | 13515 | 0.3364 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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