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bert-finetuned-propaganda-18
This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6542
- Precision: 0.0924
- Recall: 0.0470
- F1: 0.0623
- Accuracy: 0.8836
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: 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
Training results
Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
---|---|---|---|---|---|---|---|
0.6679 | 1.0 | 670 | 0.7379 | 0.125 | 0.0035 | 0.0069 | 0.8868 |
0.548 | 2.0 | 1340 | 0.5916 | 0.0845 | 0.0435 | 0.0574 | 0.8831 |
0.3781 | 3.0 | 2010 | 0.6542 | 0.0924 | 0.0470 | 0.0623 | 0.8836 |
Framework versions
- Transformers 4.21.3
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1