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wav2vec2-xls-r-1b-ro
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - RO dataset. It achieves the following results on the evaluation set:
- Loss: 0.1113
- Wer: 0.4770
- Cer: 0.0306
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: 3e-05
- 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: 2000
- num_epochs: 50.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.7844 | 1.67 | 1500 | 0.3412 | 0.8600 | 0.0940 |
| 0.7272 | 3.34 | 3000 | 0.1926 | 0.6409 | 0.0527 |
| 0.6924 | 5.02 | 4500 | 0.1413 | 0.5722 | 0.0401 |
| 0.6327 | 6.69 | 6000 | 0.1252 | 0.5366 | 0.0371 |
| 0.6363 | 8.36 | 7500 | 0.1235 | 0.5741 | 0.0389 |
| 0.6238 | 10.03 | 9000 | 0.1180 | 0.5542 | 0.0362 |
| 0.6018 | 11.71 | 10500 | 0.1192 | 0.5694 | 0.0369 |
| 0.583 | 13.38 | 12000 | 0.1216 | 0.5772 | 0.0385 |
| 0.5643 | 15.05 | 13500 | 0.1195 | 0.5419 | 0.0371 |
| 0.5399 | 16.72 | 15000 | 0.1240 | 0.5224 | 0.0370 |
| 0.5529 | 18.39 | 16500 | 0.1174 | 0.5555 | 0.0367 |
| 0.5246 | 20.07 | 18000 | 0.1097 | 0.5047 | 0.0339 |
| 0.4936 | 21.74 | 19500 | 0.1225 | 0.5189 | 0.0382 |
| 0.4629 | 23.41 | 21000 | 0.1142 | 0.5047 | 0.0344 |
| 0.4463 | 25.08 | 22500 | 0.1168 | 0.4887 | 0.0339 |
| 0.4671 | 26.76 | 24000 | 0.1119 | 0.5073 | 0.0338 |
| 0.4359 | 28.43 | 25500 | 0.1206 | 0.5479 | 0.0363 |
| 0.4225 | 30.1 | 27000 | 0.1122 | 0.5170 | 0.0345 |
| 0.4038 | 31.77 | 28500 | 0.1159 | 0.5032 | 0.0343 |
| 0.4271 | 33.44 | 30000 | 0.1116 | 0.5126 | 0.0339 |
| 0.3867 | 35.12 | 31500 | 0.1101 | 0.4937 | 0.0327 |
| 0.3674 | 36.79 | 33000 | 0.1142 | 0.4940 | 0.0330 |
| 0.3607 | 38.46 | 34500 | 0.1106 | 0.5145 | 0.0327 |
| 0.3651 | 40.13 | 36000 | 0.1172 | 0.4921 | 0.0317 |
| 0.3268 | 41.81 | 37500 | 0.1093 | 0.4830 | 0.0310 |
| 0.3345 | 43.48 | 39000 | 0.1131 | 0.4760 | 0.0314 |
| 0.3236 | 45.15 | 40500 | 0.1132 | 0.4864 | 0.0317 |
| 0.312 | 46.82 | 42000 | 0.1124 | 0.4861 | 0.0315 |
| 0.3106 | 48.49 | 43500 | 0.1116 | 0.4745 | 0.0306 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
