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wav2vec2-large-xls-r-300m-irish-colab_test
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: 1.7839
- Wer: 0.6220
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: 100
- num_epochs: 90
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 10.0428 | 2.94 | 50 | 4.1311 | 1.0 |
| 3.2917 | 5.88 | 100 | 3.1468 | 1.0 |
| 3.0221 | 8.82 | 150 | 2.9848 | 1.0 |
| 2.9795 | 11.76 | 200 | 2.9567 | 1.0 |
| 2.9379 | 14.71 | 250 | 2.9463 | 1.0 |
| 2.9068 | 17.65 | 300 | 2.8330 | 1.0 |
| 2.5088 | 20.59 | 350 | 1.9807 | 0.9535 |
| 1.6188 | 23.53 | 400 | 1.4254 | 0.8398 |
| 1.0435 | 26.47 | 450 | 1.3668 | 0.7807 |
| 0.7212 | 29.41 | 500 | 1.3914 | 0.7476 |
| 0.5456 | 32.35 | 550 | 1.5495 | 0.7470 |
| 0.4297 | 35.29 | 600 | 1.4751 | 0.6960 |
| 0.3533 | 38.24 | 650 | 1.5157 | 0.6909 |
| 0.2899 | 41.18 | 700 | 1.5394 | 0.6879 |
| 0.2529 | 44.12 | 750 | 1.6186 | 0.6903 |
| 0.2413 | 47.06 | 800 | 1.6386 | 0.6954 |
| 0.2113 | 50.0 | 850 | 1.6906 | 0.6778 |
| 0.1769 | 52.94 | 900 | 1.6918 | 0.6575 |
| 0.1622 | 55.88 | 950 | 1.7313 | 0.6572 |
| 0.1564 | 58.82 | 1000 | 1.7701 | 0.6510 |
| 0.1637 | 61.76 | 1050 | 1.6800 | 0.6444 |
| 0.148 | 64.71 | 1100 | 1.7306 | 0.6477 |
| 0.1385 | 67.65 | 1150 | 1.7605 | 0.6408 |
| 0.1264 | 70.59 | 1200 | 1.7534 | 0.6244 |
| 0.1157 | 73.53 | 1250 | 1.7906 | 0.6381 |
| 0.1027 | 76.47 | 1300 | 1.7803 | 0.6265 |
| 0.1061 | 79.41 | 1350 | 1.7617 | 0.6259 |
| 0.0934 | 82.35 | 1400 | 1.7649 | 0.6253 |
| 0.0904 | 85.29 | 1450 | 1.7713 | 0.6187 |
| 0.0911 | 88.24 | 1500 | 1.7839 | 0.6220 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.10.3
