wav2vec2-base-1
This model is a fine-tuned version of facebook/wav2vec2-base on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.9254
- Wer: 0.3216
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: 0.0001
- train_batch_size: 32
- 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: 1000
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.6597 | 2.2 | 1000 | 0.8904 | 0.5388 |
0.4751 | 4.41 | 2000 | 0.7009 | 0.3976 |
0.3307 | 6.61 | 3000 | 0.7068 | 0.3672 |
0.2574 | 8.81 | 4000 | 0.7320 | 0.3544 |
0.2096 | 11.01 | 5000 | 0.7803 | 0.3418 |
0.177 | 13.22 | 6000 | 0.7768 | 0.3423 |
0.1521 | 15.42 | 7000 | 0.8113 | 0.3375 |
0.1338 | 17.62 | 8000 | 0.8153 | 0.3325 |
0.1168 | 19.82 | 9000 | 0.8851 | 0.3306 |
0.104 | 22.03 | 10000 | 0.8811 | 0.3277 |
0.0916 | 24.23 | 11000 | 0.8722 | 0.3254 |
0.083 | 26.43 | 12000 | 0.9527 | 0.3265 |
0.0766 | 28.63 | 13000 | 0.9254 | 0.3216 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.13.3
- Tokenizers 0.10.3
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