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wav2vec2-xls-r-common_voice-tr-ft
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:
- Loss: 0.3736
- Wer: 0.2930
- Cer: 0.0708
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: 0.0005
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 96
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.5462 | 13.51 | 500 | 0.4423 | 0.4807 | 0.1188 |
| 0.342 | 27.03 | 1000 | 0.3781 | 0.3954 | 0.0967 |
| 0.2272 | 40.54 | 1500 | 0.3816 | 0.3595 | 0.0893 |
| 0.1805 | 54.05 | 2000 | 0.3943 | 0.3487 | 0.0854 |
| 0.1318 | 67.57 | 2500 | 0.3818 | 0.3262 | 0.0801 |
| 0.1213 | 81.08 | 3000 | 0.3777 | 0.3113 | 0.0758 |
| 0.0639 | 94.59 | 3500 | 0.3788 | 0.2953 | 0.0716 |
Framework versions
- Transformers 4.14.1
- Pytorch 1.8.0
- Datasets 1.17.0
- Tokenizers 0.10.3
