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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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datasets: |
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- sem_eval_2018_task_1 |
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metrics: |
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- f1 |
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- accuracy |
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model-index: |
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- name: bert-finetuned-sem_eval-english |
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results: |
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- task: |
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name: Text Classification |
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type: text-classification |
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dataset: |
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name: sem_eval_2018_task_1 |
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type: sem_eval_2018_task_1 |
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config: subtask5.english |
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split: validation |
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args: subtask5.english |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.7075236671649229 |
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- name: Accuracy |
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type: accuracy |
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value: 0.28555304740406323 |
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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-finetuned-sem_eval-english |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the sem_eval_2018_task_1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3008 |
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- F1: 0.7075 |
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- Roc Auc: 0.8000 |
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- Accuracy: 0.2856 |
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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: 8 |
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- eval_batch_size: 8 |
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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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:| |
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| 0.3964 | 1.0 | 855 | 0.3197 | 0.6852 | 0.7849 | 0.2810 | |
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| 0.2788 | 2.0 | 1710 | 0.3039 | 0.7049 | 0.7978 | 0.2912 | |
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| 0.2347 | 3.0 | 2565 | 0.3008 | 0.7075 | 0.8000 | 0.2856 | |
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| 0.2094 | 4.0 | 3420 | 0.3091 | 0.7041 | 0.7976 | 0.2856 | |
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| 0.1886 | 5.0 | 4275 | 0.3122 | 0.7068 | 0.8011 | 0.2810 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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