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finetuned_roberta-base-on-IEMOCAP_2
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-emotion on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8093
- Accuracy: 0.7283
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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9868 | 1.0 | 113 | 0.9133 | 0.6493 |
| 0.7065 | 2.0 | 226 | 0.8576 | 0.6803 |
| 0.4773 | 3.0 | 339 | 0.8821 | 0.6947 |
| 0.4002 | 4.0 | 452 | 0.9283 | 0.7024 |
| 0.3338 | 5.0 | 565 | 1.0637 | 0.6792 |
| 0.3128 | 6.0 | 678 | 1.0653 | 0.6892 |
| 0.2552 | 7.0 | 791 | 1.1852 | 0.6814 |
| 0.244 | 8.0 | 904 | 1.2298 | 0.6825 |
| 0.2178 | 9.0 | 1017 | 1.2453 | 0.6925 |
| 0.2083 | 10.0 | 1130 | 1.3690 | 0.6858 |
| 0.1516 | 11.0 | 1243 | 1.3877 | 0.6914 |
| 0.1186 | 12.0 | 1356 | 1.4572 | 0.6903 |
| 0.1681 | 13.0 | 1469 | 1.4289 | 0.6925 |
| 0.1175 | 14.0 | 1582 | 1.4813 | 0.6869 |
| 0.1068 | 15.0 | 1695 | 1.4878 | 0.6869 |
Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1
