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--- |
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license: apache-2.0 |
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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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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: 0.6645074224021592 |
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- name: Accuracy |
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type: accuracy |
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value: 0.2595936794582393 |
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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: 0.3308 |
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- F1: 0.6645 |
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- Roc Auc: 0.7642 |
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- Accuracy: 0.2596 |
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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: 1 |
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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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| 0.4155 | 1.0 | 855 | 0.3308 | 0.6645 | 0.7642 | 0.2596 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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