bert-base-uncased-IBM-argQ-30k-finetuned-convincingness-acl2016
This model is a fine-tuned version of jakub014/bert-base-uncased-IBM-argQ-30k on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4143
- Accuracy: 0.9266
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 |
---|---|---|---|---|
0.3496 | 1.0 | 583 | 0.2207 | 0.9133 |
0.1779 | 2.0 | 1166 | 0.2128 | 0.9159 |
0.1439 | 3.0 | 1749 | 0.3202 | 0.9262 |
0.0903 | 4.0 | 2332 | 0.4013 | 0.9258 |
0.051 | 5.0 | 2915 | 0.4143 | 0.9266 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
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