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wav2vec2-large-multilang-cv-ru
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.9734
- Wer: 0.7037
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 6.0328 | 0.79 | 500 | 3.0713 | 1.0 |
| 1.9426 | 1.58 | 1000 | 1.2048 | 0.9963 |
| 1.1285 | 2.37 | 1500 | 0.9825 | 0.9282 |
| 0.9462 | 3.15 | 2000 | 0.8836 | 0.8965 |
| 0.8274 | 3.94 | 2500 | 0.8134 | 0.8661 |
| 0.7106 | 4.73 | 3000 | 0.8033 | 0.8387 |
| 0.6545 | 5.52 | 3500 | 0.8309 | 0.8366 |
| 0.6013 | 6.31 | 4000 | 0.7667 | 0.8240 |
| 0.5599 | 7.1 | 4500 | 0.7740 | 0.8160 |
| 0.5027 | 7.89 | 5000 | 0.7796 | 0.8188 |
| 0.4588 | 8.68 | 5500 | 0.8204 | 0.7968 |
| 0.4448 | 9.46 | 6000 | 0.8277 | 0.7738 |
| 0.4122 | 10.25 | 6500 | 0.8292 | 0.7776 |
| 0.3816 | 11.04 | 7000 | 0.8548 | 0.7907 |
| 0.3587 | 11.83 | 7500 | 0.8245 | 0.7805 |
| 0.3374 | 12.62 | 8000 | 0.8371 | 0.7701 |
| 0.3214 | 13.41 | 8500 | 0.8311 | 0.7822 |
| 0.3072 | 14.2 | 9000 | 0.8940 | 0.7674 |
| 0.2929 | 14.98 | 9500 | 0.8788 | 0.7604 |
| 0.257 | 15.77 | 10000 | 0.8911 | 0.7633 |
| 0.2592 | 16.56 | 10500 | 0.8673 | 0.7604 |
| 0.2392 | 17.35 | 11000 | 0.9582 | 0.7810 |
| 0.232 | 18.14 | 11500 | 0.9340 | 0.7423 |
| 0.2252 | 18.93 | 12000 | 0.8874 | 0.7320 |
| 0.2079 | 19.72 | 12500 | 0.9436 | 0.7483 |
| 0.2003 | 20.5 | 13000 | 0.9573 | 0.7638 |
| 0.194 | 21.29 | 13500 | 0.9361 | 0.7308 |
| 0.188 | 22.08 | 14000 | 0.9704 | 0.7221 |
| 0.1754 | 22.87 | 14500 | 0.9668 | 0.7265 |
| 0.1688 | 23.66 | 15000 | 0.9680 | 0.7246 |
| 0.162 | 24.45 | 15500 | 0.9443 | 0.7066 |
| 0.1617 | 25.24 | 16000 | 0.9664 | 0.7265 |
| 0.1504 | 26.03 | 16500 | 0.9505 | 0.7189 |
| 0.1425 | 26.81 | 17000 | 0.9536 | 0.7112 |
| 0.134 | 27.6 | 17500 | 0.9674 | 0.7047 |
| 0.1301 | 28.39 | 18000 | 0.9852 | 0.7066 |
| 0.1314 | 29.18 | 18500 | 0.9766 | 0.7073 |
| 0.1219 | 29.97 | 19000 | 0.9734 | 0.7037 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1
