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distilbert-magazine-classifier
This model is a fine-tuned version of distilbert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8377
- Precision: 0.25
- Recall: 0.125
- Fscore: 0.1667
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: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Fscore |
|---|---|---|---|---|---|---|
| 0.1779 | 1.0 | 2 | 1.7584 | 0.2222 | 0.3333 | 0.2667 |
| 0.1635 | 2.0 | 4 | 1.7585 | 0.25 | 0.125 | 0.1667 |
| 0.1405 | 3.0 | 6 | 1.8377 | 0.25 | 0.125 | 0.1667 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3
