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bert-base-uncased-finetuned-convincingness-IBM
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6537
- Accuracy: 0.7511
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
No log | 1.0 | 270 | 0.5707 | 0.7337 |
0.4673 | 2.0 | 540 | 0.6059 | 0.7221 |
0.4673 | 3.0 | 810 | 0.6537 | 0.7511 |
0.2218 | 4.0 | 1080 | 0.8485 | 0.7467 |
0.2218 | 5.0 | 1350 | 0.9221 | 0.7438 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2