wavlm-finetuned-IEMOCAP
This model is a fine-tuned version of microsoft/wavlm-base-plus on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4042
- Accuracy: 0.4972
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 6.8687 | 1.0 | 402 | 1.7019 | 0.3292 |
| 6.5214 | 2.0 | 804 | 1.6125 | 0.3671 |
| 5.9374 | 3.0 | 1206 | 1.5022 | 0.4493 |
| 5.4183 | 4.0 | 1608 | 1.4527 | 0.4798 |
| 5.2812 | 5.0 | 2010 | 1.4042 | 0.4972 |
Framework versions
- Transformers 5.12.0
- Pytorch 2.11.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2