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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- elsevier-oa-cc-by |
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model-index: |
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- name: roberta-base-finetuned-academic |
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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-base-finetuned-academic |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the elsevier-oa-cc-by dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1158 |
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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: 0.0001 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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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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- num_epochs: 5 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 2.1903 | 0.25 | 1025 | 2.0998 | |
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| 2.1752 | 0.5 | 2050 | 2.1186 | |
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| 2.1864 | 0.75 | 3075 | 2.1073 | |
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| 2.1874 | 1.0 | 4100 | 2.1177 | |
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| 2.1669 | 1.25 | 5125 | 2.1091 | |
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| 2.1859 | 1.5 | 6150 | 2.1212 | |
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| 2.1783 | 1.75 | 7175 | 2.1096 | |
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| 2.1734 | 2.0 | 8200 | 2.0998 | |
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| 2.1712 | 2.25 | 9225 | 2.0972 | |
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| 2.1812 | 2.5 | 10250 | 2.1051 | |
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| 2.1811 | 2.75 | 11275 | 2.1150 | |
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| 2.1826 | 3.0 | 12300 | 2.1097 | |
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| 2.172 | 3.25 | 13325 | 2.1115 | |
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| 2.1745 | 3.5 | 14350 | 2.1098 | |
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| 2.1758 | 3.75 | 15375 | 2.1101 | |
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| 2.1834 | 4.0 | 16400 | 2.1232 | |
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| 2.1836 | 4.25 | 17425 | 2.1052 | |
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| 2.1791 | 4.5 | 18450 | 2.1186 | |
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| 2.172 | 4.75 | 19475 | 2.1039 | |
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| 2.1797 | 5.0 | 20500 | 2.1015 | |
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### Framework versions |
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- Transformers 4.19.0.dev0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.3.2 |
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- Tokenizers 0.12.1 |
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