FakeNews-deberta-large-stable
This model is a fine-tuned version of microsoft/deberta-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1048
- Accuracy: 0.9771
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3373 | 1.0 | 802 | 0.1635 | 0.9682 |
| 0.0951 | 2.0 | 1605 | 0.1048 | 0.9771 |
| 0.0419 | 3.0 | 2407 | 0.1141 | 0.9785 |
| 0.0114 | 4.0 | 3210 | 0.1555 | 0.9818 |
| 0.0026 | 5.0 | 4010 | 0.1680 | 0.9808 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
microsoft/deberta-large