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wav2vec2-large-xls-r-300m-hi
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: 2.4156
- Wer: 0.7181
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: 500
- num_epochs: 30
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
5.7703 | 2.72 | 400 | 2.2274 | 0.9259 |
0.6515 | 5.44 | 800 | 1.5812 | 0.7581 |
0.339 | 8.16 | 1200 | 2.0590 | 0.7825 |
0.2262 | 10.88 | 1600 | 2.0324 | 0.7603 |
0.1665 | 13.6 | 2000 | 2.1396 | 0.7481 |
0.1311 | 16.33 | 2400 | 2.2090 | 0.7379 |
0.1079 | 19.05 | 2800 | 2.3907 | 0.7612 |
0.0927 | 21.77 | 3200 | 2.5294 | 0.7478 |
0.0748 | 24.49 | 3600 | 2.5024 | 0.7452 |
0.0644 | 27.21 | 4000 | 2.4715 | 0.7307 |
0.0569 | 29.93 | 4400 | 2.4156 | 0.7181 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3