wav2vec2-large-xls-r-300m-lg
This model is a fine-tuned version of Alvin-Nahabwe/wav2vec2-large-xls-r-300m-gn on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2283
- Wer: 0.1569
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: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 22
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.2883 | 1.39 | 400 | 0.2180 | 0.2128 |
0.2603 | 2.78 | 800 | 0.2108 | 0.2082 |
0.2341 | 4.17 | 1200 | 0.2127 | 0.2085 |
0.2194 | 5.56 | 1600 | 0.2004 | 0.2050 |
0.1846 | 6.95 | 2000 | 0.1961 | 0.1898 |
0.1627 | 8.34 | 2400 | 0.1919 | 0.1779 |
0.1464 | 9.75 | 2800 | 0.1867 | 0.1677 |
0.1273 | 11.14 | 3200 | 0.1949 | 0.1710 |
0.1153 | 12.53 | 3600 | 0.1965 | 0.1639 |
0.1006 | 13.93 | 4000 | 0.1983 | 0.1603 |
0.1056 | 15.32 | 4400 | 0.2159 | 0.1686 |
0.1011 | 16.71 | 4800 | 0.2104 | 0.1663 |
0.0895 | 18.1 | 5200 | 0.2211 | 0.1634 |
0.0818 | 19.49 | 5600 | 0.2234 | 0.1610 |
0.0778 | 20.88 | 6000 | 0.2283 | 0.1569 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
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