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xls-r-300m-pa
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - PA-IN dataset. It achieves the following results on the evaluation set:
- Loss: 1.0443
- Wer: 0.5715
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: 7.5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 2000
- num_epochs: 500.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.6694 | 19.22 | 500 | 4.0455 | 1.0 |
| 3.3907 | 38.45 | 1000 | 3.2836 | 1.0 |
| 2.0866 | 57.67 | 1500 | 1.2788 | 0.7715 |
| 1.4106 | 76.9 | 2000 | 0.7866 | 0.6891 |
| 1.1711 | 96.15 | 2500 | 0.6556 | 0.6272 |
| 1.038 | 115.37 | 3000 | 0.6195 | 0.5680 |
| 0.8989 | 134.6 | 3500 | 0.6563 | 0.5602 |
| 0.8021 | 153.82 | 4000 | 0.6644 | 0.5327 |
| 0.7161 | 173.07 | 4500 | 0.6844 | 0.5253 |
| 0.6449 | 192.3 | 5000 | 0.7018 | 0.5331 |
| 0.5659 | 211.52 | 5500 | 0.7451 | 0.5465 |
| 0.5118 | 230.75 | 6000 | 0.7857 | 0.5386 |
| 0.4385 | 249.97 | 6500 | 0.8062 | 0.5382 |
| 0.3984 | 269.22 | 7000 | 0.8316 | 0.5621 |
| 0.3666 | 288.45 | 7500 | 0.8736 | 0.5504 |
| 0.3256 | 307.67 | 8000 | 0.9133 | 0.5688 |
| 0.289 | 326.9 | 8500 | 0.9556 | 0.5684 |
| 0.2663 | 346.15 | 9000 | 0.9344 | 0.5708 |
| 0.2445 | 365.37 | 9500 | 0.9472 | 0.5590 |
| 0.2289 | 384.6 | 10000 | 0.9713 | 0.5672 |
| 0.2048 | 403.82 | 10500 | 0.9978 | 0.5762 |
| 0.1857 | 423.07 | 11000 | 1.0230 | 0.5798 |
| 0.1751 | 442.3 | 11500 | 1.0409 | 0.5755 |
| 0.1688 | 461.52 | 12000 | 1.0445 | 0.5727 |
| 0.1633 | 480.75 | 12500 | 1.0484 | 0.5739 |
| 0.1488 | 499.97 | 13000 | 1.0443 | 0.5715 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
