hubert-finetuned-emotion-audio-dataset
This model is a fine-tuned version of facebook/hubert-base-ls960 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5474
- Accuracy: 0.8289
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 |
|---|---|---|---|---|
| 5.1336 | 1.0 | 640 | 1.0654 | 0.6492 |
| 3.4287 | 2.0 | 1280 | 0.7009 | 0.7629 |
| 2.3725 | 3.0 | 1920 | 0.6202 | 0.7965 |
| 2.1159 | 4.0 | 2560 | 0.5752 | 0.8121 |
| 1.7476 | 5.0 | 3200 | 0.5474 | 0.8289 |
Framework versions
- Transformers 5.10.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2