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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: cola-teacher |
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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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# cola-teacher |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3687 |
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- Accuracy: 0.8207 |
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- F1: 0.8793 |
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- Precision: 0.8225 |
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- Recall: 0.9445 |
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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 | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.5177 | 1.0 | 535 | 0.4576 | 0.7977 | 0.8677 | 0.7918 | 0.9598 | |
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| 0.3187 | 2.0 | 1070 | 0.4655 | 0.8159 | 0.8764 | 0.8175 | 0.9445 | |
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| 0.2035 | 3.0 | 1605 | 0.6732 | 0.8111 | 0.8731 | 0.8149 | 0.9404 | |
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| 0.1495 | 4.0 | 2140 | 0.9194 | 0.8130 | 0.8751 | 0.8131 | 0.9473 | |
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| 0.1041 | 5.0 | 2675 | 0.9687 | 0.8226 | 0.8819 | 0.8168 | 0.9584 | |
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| 0.0823 | 6.0 | 3210 | 1.1245 | 0.8226 | 0.8804 | 0.8245 | 0.9445 | |
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| 0.0552 | 7.0 | 3745 | 1.0909 | 0.8274 | 0.8834 | 0.8287 | 0.9459 | |
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| 0.0427 | 8.0 | 4280 | 1.2896 | 0.8236 | 0.8808 | 0.8262 | 0.9431 | |
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| 0.0278 | 9.0 | 4815 | 1.3355 | 0.8226 | 0.8804 | 0.8245 | 0.9445 | |
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| 0.023 | 10.0 | 5350 | 1.3687 | 0.8207 | 0.8793 | 0.8225 | 0.9445 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.4.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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