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wav2vec2-large-xls-r-300m-tr-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.4316
- Wer: 0.2905
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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.9953 | 3.67 | 400 | 0.7024 | 0.7226 |
| 0.4046 | 7.34 | 800 | 0.4342 | 0.5343 |
| 0.201 | 11.01 | 1200 | 0.4396 | 0.5290 |
| 0.1513 | 14.68 | 1600 | 0.4319 | 0.4108 |
| 0.1285 | 18.35 | 2000 | 0.4422 | 0.3864 |
| 0.1086 | 22.02 | 2400 | 0.4568 | 0.3796 |
| 0.0998 | 25.69 | 2800 | 0.4687 | 0.3732 |
| 0.0863 | 29.36 | 3200 | 0.4726 | 0.3803 |
| 0.0809 | 33.03 | 3600 | 0.4479 | 0.3601 |
| 0.0747 | 36.7 | 4000 | 0.4624 | 0.3525 |
| 0.0692 | 40.37 | 4400 | 0.4366 | 0.3435 |
| 0.0595 | 44.04 | 4800 | 0.4204 | 0.3510 |
| 0.0584 | 47.71 | 5200 | 0.4202 | 0.3402 |
| 0.0545 | 51.38 | 5600 | 0.4366 | 0.3343 |
| 0.0486 | 55.05 | 6000 | 0.4492 | 0.3678 |
| 0.0444 | 58.72 | 6400 | 0.4471 | 0.3301 |
| 0.0406 | 62.39 | 6800 | 0.4382 | 0.3318 |
| 0.0341 | 66.06 | 7200 | 0.4295 | 0.3258 |
| 0.0297 | 69.72 | 7600 | 0.4336 | 0.3205 |
| 0.0295 | 73.39 | 8000 | 0.4240 | 0.3199 |
| 0.0261 | 77.06 | 8400 | 0.4316 | 0.3143 |
| 0.0247 | 80.73 | 8800 | 0.4300 | 0.3165 |
| 0.0207 | 84.4 | 9200 | 0.4380 | 0.3111 |
| 0.0203 | 88.07 | 9600 | 0.4218 | 0.2998 |
| 0.0174 | 91.74 | 10000 | 0.4271 | 0.2973 |
| 0.015 | 95.41 | 10400 | 0.4330 | 0.2939 |
| 0.0144 | 99.08 | 10800 | 0.4316 | 0.2905 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu102
- Datasets 2.5.2
- Tokenizers 0.13.1
