speech_emotion_is25
This model is a fine-tuned version of sridhar1ga/speech_emotion_is25 on an unknown dataset. It achieves the following results on the evaluation set:
- F1: 0.1507
- Loss: 1.9786
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: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | F1 | Validation Loss |
|---|---|---|---|---|
| 8.3207 | 1.0 | 73 | 0.0288 | 2.0793 |
| 8.3072 | 2.0 | 146 | 0.0379 | 2.0790 |
| 8.2824 | 3.0 | 219 | 0.1134 | 2.0707 |
| 8.178 | 4.0 | 292 | 0.1204 | 2.0244 |
| 8.0941 | 5.0 | 365 | 0.1380 | 2.0037 |
| 8.0498 | 6.0 | 438 | 0.1395 | 1.9927 |
| 7.9997 | 7.0 | 511 | 0.1379 | 1.9860 |
| 7.9315 | 8.0 | 584 | 0.1485 | 1.9829 |
| 7.9988 | 9.0 | 657 | 0.1464 | 1.9797 |
| 7.9838 | 9.8690 | 720 | 0.1507 | 1.9786 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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