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--- |
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library_name: transformers |
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license: mit |
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base_model: roberta-large |
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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-atomic-anion-1e-06-256 |
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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-atomic-anion-1e-06-256 |
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This model is a fine-tuned version of [roberta-large](https://huggingface.co/roberta-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3194 |
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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: 256 |
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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: 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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| 0.4954 | 1.0 | 1152 | 0.4666 | |
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| 0.4156 | 2.0 | 2304 | 0.4036 | |
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| 0.3791 | 3.0 | 3456 | 0.3861 | |
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| 0.3586 | 4.0 | 4608 | 0.3600 | |
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| 0.3372 | 5.0 | 5760 | 0.3483 | |
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| 0.3232 | 6.0 | 6912 | 0.3380 | |
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| 0.3075 | 7.0 | 8064 | 0.3362 | |
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| 0.2964 | 8.0 | 9216 | 0.3308 | |
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| 0.2811 | 9.0 | 10368 | 0.3284 | |
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| 0.2733 | 10.0 | 11520 | 0.3240 | |
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| 0.2668 | 11.0 | 12672 | 0.3204 | |
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| 0.2608 | 12.0 | 13824 | 0.3210 | |
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| 0.2509 | 13.0 | 14976 | 0.3186 | |
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| 0.2426 | 14.0 | 16128 | 0.3173 | |
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| 0.2358 | 15.0 | 17280 | 0.3191 | |
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| 0.2307 | 16.0 | 18432 | 0.3205 | |
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| 0.232 | 17.0 | 19584 | 0.3149 | |
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| 0.2264 | 18.0 | 20736 | 0.3174 | |
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| 0.2199 | 19.0 | 21888 | 0.3199 | |
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| 0.2188 | 20.0 | 23040 | 0.3194 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.1 |
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