bert-imdb
This model is a fine-tuned version of bert-base-uncased on the imdb dataset. It achieves the following results on the evaluation set:
- Loss: 0.2266
- Accuracy: 0.9396
- F1: 0.9396
- Precision: 0.9397
- Recall: 0.9396
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 9072
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
0.2223 | 1.0 | 1563 | 0.1898 | 0.9328 | 0.9327 | 0.9331 | 0.9328 |
0.1161 | 2.0 | 3126 | 0.2266 | 0.9396 | 0.9396 | 0.9397 | 0.9396 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
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Model tree for JeffreyJIANG/bert-imdb
Base model
google-bert/bert-base-uncasedDataset used to train JeffreyJIANG/bert-imdb
Evaluation results
- Accuracy on imdbtest set self-reported0.940
- F1 on imdbtest set self-reported0.940
- Precision on imdbtest set self-reported0.940
- Recall on imdbtest set self-reported0.940