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wav2vec2-large-xls-r-300m-euskera-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: 0.1873
- Wer: 0.1752
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 2.5827 | 0.76 | 600 | 0.3985 | 0.5778 |
| 0.2963 | 1.51 | 1200 | 0.2492 | 0.4142 |
| 0.2122 | 2.27 | 1800 | 0.2132 | 0.3133 |
| 0.1686 | 3.03 | 2400 | 0.2078 | 0.2851 |
| 0.1373 | 3.79 | 3000 | 0.1910 | 0.2750 |
| 0.1254 | 4.54 | 3600 | 0.1850 | 0.2619 |
| 0.1137 | 5.3 | 4200 | 0.1874 | 0.2503 |
| 0.1008 | 6.06 | 4800 | 0.1857 | 0.2554 |
| 0.0934 | 6.81 | 5400 | 0.1844 | 0.2404 |
| 0.0876 | 7.57 | 6000 | 0.2001 | 0.2375 |
| 0.0801 | 8.33 | 6600 | 0.2036 | 0.2512 |
| 0.0732 | 9.09 | 7200 | 0.1921 | 0.2301 |
| 0.069 | 9.84 | 7800 | 0.1821 | 0.2330 |
| 0.0628 | 10.6 | 8400 | 0.1915 | 0.2249 |
| 0.0619 | 11.36 | 9000 | 0.1881 | 0.2113 |
| 0.0549 | 12.11 | 9600 | 0.1920 | 0.2076 |
| 0.0524 | 12.87 | 10200 | 0.1901 | 0.2079 |
| 0.0492 | 13.63 | 10800 | 0.1767 | 0.2020 |
| 0.0445 | 14.38 | 11400 | 0.1852 | 0.1933 |
| 0.0427 | 15.14 | 12000 | 0.1995 | 0.1994 |
| 0.0398 | 15.9 | 12600 | 0.1922 | 0.1932 |
| 0.037 | 16.66 | 13200 | 0.1956 | 0.1920 |
| 0.0353 | 17.41 | 13800 | 0.1990 | 0.1909 |
| 0.0327 | 18.17 | 14400 | 0.1906 | 0.1784 |
| 0.0311 | 18.93 | 15000 | 0.1847 | 0.1765 |
| 0.0295 | 19.68 | 15600 | 0.1873 | 0.1752 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
