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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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- rotten_tomatoes_movie_review |
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metrics: |
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- accuracy |
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- f1 |
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model-index: |
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- name: bert-base-cased-finetuned-rotten-tomatoes-epochs-5 |
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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: rotten_tomatoes_movie_review |
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type: rotten_tomatoes_movie_review |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.975609756097561 |
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- name: F1 |
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type: f1 |
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value: 0.9756096702430234 |
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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-base-cased-finetuned-rotten-tomatoes-epochs-5 |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the rotten_tomatoes_movie_review dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1022 |
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- Accuracy: 0.9756 |
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- F1: 0.9756 |
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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: 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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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 0.595 | 1.0 | 34 | 0.3926 | 0.8780 | 0.8780 | |
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| 0.3767 | 2.0 | 68 | 0.2374 | 0.9390 | 0.9390 | |
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| 0.273 | 3.0 | 102 | 0.1522 | 0.9615 | 0.9615 | |
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| 0.1597 | 4.0 | 136 | 0.1154 | 0.9719 | 0.9719 | |
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| 0.1348 | 5.0 | 170 | 0.1022 | 0.9756 | 0.9756 | |
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### Framework versions |
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- Transformers 4.16.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 1.16.1 |
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- Tokenizers 0.15.0 |
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