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This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - FR dataset. It achieves the following results on the evaluation set:
- Loss: 0.2464
- Wer: 0.2220
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: 7.5e-05
- 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: 2000
- num_epochs: 5.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.0326 | 0.32 | 1000 | 0.3092 | 0.2718 |
1.0828 | 0.65 | 2000 | 0.2843 | 0.2606 |
1.0771 | 0.97 | 3000 | 0.2774 | 0.2488 |
1.0306 | 1.3 | 4000 | 0.2588 | 0.2351 |
1.0052 | 1.62 | 5000 | 0.2483 | 0.2284 |
0.9865 | 1.94 | 6000 | 0.2464 | 0.2220 |
0.978 | 2.27 | 7000 | 0.2514 | 0.2172 |
1.7438 | 2.59 | 8000 | 0.7983 | 0.5072 |
2.3309 | 2.92 | 9000 | 1.8917 | 0.9416 |
2.1834 | 3.24 | 10000 | 1.7496 | 0.9030 |
2.3047 | 3.56 | 11000 | 1.5377 | 0.8747 |
2.1378 | 3.89 | 12000 | 1.3501 | 0.7923 |
1.9812 | 4.21 | 13000 | 1.2662 | 0.7697 |
2.6855 | 4.54 | 14000 | 2.4120 | 0.9902 |
2.7482 | 4.86 | 15000 | 2.5341 | 0.9874 |
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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