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my_Misinformation_distilbert_model
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1879
- Accuracy: 0.9661
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 214 | 0.1283 | 0.9544 |
| No log | 2.0 | 428 | 0.1528 | 0.9498 |
| 0.1645 | 3.0 | 642 | 0.1276 | 0.9685 |
| 0.1645 | 4.0 | 856 | 0.1650 | 0.9614 |
| 0.0306 | 5.0 | 1070 | 0.1653 | 0.9661 |
| 0.0306 | 6.0 | 1284 | 0.1739 | 0.9673 |
| 0.0306 | 7.0 | 1498 | 0.1771 | 0.9661 |
| 0.0053 | 8.0 | 1712 | 0.1795 | 0.9661 |
| 0.0053 | 9.0 | 1926 | 0.1860 | 0.9626 |
| 0.0018 | 10.0 | 2140 | 0.1879 | 0.9661 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
