ColD-Fusion-finetuned-convincingness-acl2016
This model is a fine-tuned version of ibm/ColD-Fusion on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4112
- Accuracy: 0.9275
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 |
|---|---|---|---|---|
| 0.4318 | 1.0 | 583 | 0.2267 | 0.9047 |
| 0.2063 | 2.0 | 1166 | 0.1945 | 0.9142 |
| 0.1647 | 3.0 | 1749 | 0.3107 | 0.9155 |
| 0.1179 | 4.0 | 2332 | 0.3730 | 0.9215 |
| 0.0669 | 5.0 | 2915 | 0.4112 | 0.9275 |
Framework versions
- Transformers 4.27.2
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2