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--- |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: bert_gec_detect |
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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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# bert_gec_detect |
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This model was trained from scratch on the QALB GEC dataset for a binary classification task, which is classifying whether a generated/given text is grammatically sound/correct. |
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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: 16 |
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- eval_batch_size: 16 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 0.2169 | 1.0 | 1864 | 0.2219 | 0.9330 | |
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| 0.1933 | 2.0 | 3728 | 0.2413 | 0.9321 | |
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| 0.1632 | 3.0 | 5592 | 0.2905 | 0.9295 | |
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| 0.1323 | 4.0 | 7456 | 0.2807 | 0.9346 | |
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| 0.1168 | 5.0 | 9320 | 0.3174 | 0.9334 | |
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| 0.1018 | 6.0 | 11184 | 0.3848 | 0.9346 | |
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| 0.0688 | 7.0 | 13048 | 0.4739 | 0.9325 | |
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| 0.0585 | 8.0 | 14912 | 0.4750 | 0.9347 | |
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| 0.0545 | 9.0 | 16776 | 0.4894 | 0.9337 | |
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| 0.0497 | 10.0 | 18640 | 0.5135 | 0.9349 | |
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### Framework versions |
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- Transformers 4.35.2 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.7 |
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- Tokenizers 0.15.0 |
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