wav2vec2-cls-r-300m-fr
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the COMMON_VOICE - FR dataset. It achieves the following results on the evaluation set:
- Loss: 0.6521
- Wer: 0.4330
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
2.6773 | 0.8 | 500 | 1.3907 | 0.9864 |
0.9526 | 1.6 | 1000 | 0.7760 | 0.6448 |
0.6418 | 2.4 | 1500 | 0.7605 | 0.6194 |
0.5028 | 3.2 | 2000 | 0.6516 | 0.5322 |
0.4133 | 4.0 | 2500 | 0.6303 | 0.5097 |
0.3285 | 4.8 | 3000 | 0.6422 | 0.5062 |
0.2764 | 5.6 | 3500 | 0.5936 | 0.4748 |
0.2361 | 6.4 | 4000 | 0.6486 | 0.4683 |
0.2049 | 7.2 | 4500 | 0.6321 | 0.4532 |
0.176 | 8.0 | 5000 | 0.6230 | 0.4482 |
0.1393 | 8.8 | 5500 | 0.6595 | 0.4403 |
0.1141 | 9.6 | 6000 | 0.6552 | 0.4348 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
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Dataset used to train samitizerxu/wav2vec2-xls-r-300m-fr
Evaluation results
- Test WER on Robust Speech Event - Dev Dataself-reported56.620
- Test WER on Robust Speech Event - Test Dataself-reported58.220