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FakeNews-bert-base-cased
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0941
- Accuracy: 0.9776
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.2801 | 1.0 | 803 | 0.1644 | 0.9664 |
0.0694 | 2.0 | 1606 | 0.0941 | 0.9776 |
0.0293 | 3.0 | 2409 | 0.1352 | 0.9799 |
0.014 | 4.0 | 3212 | 0.1233 | 0.9818 |
0.0036 | 5.0 | 4015 | 0.1357 | 0.9794 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1