FakeNews-bert-large-cased
This model is a fine-tuned version of bert-large-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6921
- Accuracy: 0.5234
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: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|
| 0.708 | 1.0 | 1605 | 0.6982 | 0.5234 |
| 0.7107 | 2.0 | 3210 | 0.7017 | 0.5234 |
| 0.7031 | 3.0 | 4815 | 0.6932 | 0.5234 |
| 0.7048 | 4.0 | 6420 | 0.6964 | 0.4766 |
| 0.7001 | 5.0 | 8025 | 0.6921 | 0.5234 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
google-bert/bert-large-cased