wav2vec2-ser
This model is a fine-tuned version of elgeish/wav2vec2-large-xlsr-53-arabic on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1711
- Accuracy: 0.5944
- Macro F1: 0.5922
- Uar: 0.5944
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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 | Uar |
|---|---|---|---|---|---|---|
| 2.4745 | 1.0 | 2261 | 1.3044 | 0.5146 | 0.5052 | 0.5145 |
| 2.3679 | 2.0 | 4522 | 1.2206 | 0.5582 | 0.5583 | 0.5581 |
| 2.4063 | 3.0 | 6783 | 1.1995 | 0.5728 | 0.5717 | 0.5727 |
| 2.3047 | 4.0 | 9044 | 1.1917 | 0.5747 | 0.5728 | 0.5747 |
| 2.3219 | 5.0 | 11305 | 1.1818 | 0.5854 | 0.5843 | 0.5853 |
| 2.1458 | 6.0 | 13566 | 1.1758 | 0.5880 | 0.5868 | 0.5880 |
| 2.1508 | 7.0 | 15827 | 1.1731 | 0.5931 | 0.5912 | 0.5931 |
| 2.3247 | 8.0 | 18088 | 1.1728 | 0.5924 | 0.5899 | 0.5924 |
| 2.1779 | 9.0 | 20349 | 1.1726 | 0.5935 | 0.5909 | 0.5935 |
| 2.2183 | 10.0 | 22610 | 1.1711 | 0.5944 | 0.5922 | 0.5944 |
Framework versions
- Transformers 5.12.1
- Pytorch 2.11.0+cu128
- Datasets 5.0.0
- Tokenizers 0.22.2