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distilbert-base-uncased_finetuned_olid_a
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: 0.3681
- Accuracy: 0.8512
- F1-macro: 0.8034
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: 64
- eval_batch_size: 64
- seed: 42
- 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-macro |
|---|---|---|---|---|---|
| 0.4827 | 1.0 | 207 | 0.3716 | 0.8570 | 0.8113 |
| 0.39 | 2.0 | 414 | 0.3681 | 0.8512 | 0.8034 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
