finetuned_iebert-base_on_shEMO_transcripts
This model is a fine-tuned version of minoosh/finetuned_bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3279
- Accuracy: 0.5367
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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.4217 | 1.0 | 75 | 1.2872 | 0.4933 |
| 1.2468 | 2.0 | 150 | 1.1732 | 0.5433 |
| 1.202 | 3.0 | 225 | 1.0937 | 0.5833 |
| 1.1722 | 4.0 | 300 | 1.1343 | 0.5767 |
| 1.1248 | 5.0 | 375 | 1.0780 | 0.58 |
| 1.0578 | 6.0 | 450 | 1.0778 | 0.59 |
| 0.9632 | 7.0 | 525 | 1.0967 | 0.59 |
| 0.8325 | 8.0 | 600 | 1.1147 | 0.5933 |
| 0.8339 | 9.0 | 675 | 1.1271 | 0.61 |
| 0.7494 | 10.0 | 750 | 1.1886 | 0.59 |
| 0.6416 | 11.0 | 825 | 1.2204 | 0.5833 |
| 0.5611 | 12.0 | 900 | 1.3593 | 0.5567 |
| 0.5421 | 13.0 | 975 | 1.3113 | 0.56 |
| 0.53 | 14.0 | 1050 | 1.3207 | 0.5733 |
| 0.4981 | 15.0 | 1125 | 1.3327 | 0.5567 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1