Wav2Vec_VinData
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.8569
- Wer: 0.3143
- Cer: 0.1316
- Syer: 0.3143
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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_BNB 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: 1000
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Syer |
|---|---|---|---|---|---|---|
| 27.7293 | 0.6591 | 500 | 3.4983 | 1.0 | 1.0 | 1.0 |
| 13.7701 | 1.3177 | 1000 | 1.4881 | 0.6608 | 0.2736 | 0.6608 |
| 11.0362 | 1.9768 | 1500 | 1.1284 | 0.4733 | 0.1992 | 0.4733 |
| 9.4754 | 2.6354 | 2000 | 0.9490 | 0.3819 | 0.1600 | 0.3819 |
| 8.2131 | 3.2940 | 2500 | 0.9020 | 0.3377 | 0.1412 | 0.3377 |
| 7.2151 | 3.9530 | 3000 | 0.8558 | 0.3147 | 0.1316 | 0.3147 |
| 7.2151 | 4.0 | 3036 | 0.8569 | 0.3143 | 0.1316 | 0.3143 |
Framework versions
- Transformers 5.16.1
- Pytorch 2.11.0+cu128
- Datasets 4.0.0
- Tokenizers 0.23.1