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wav2vec2-large-xls-r-300m-romansh-vallader
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - RM-VALLADER dataset. It achieves the following results on the evaluation set:
- Loss: 0.3155
- Wer: 0.3162
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: 7e-05
- train_batch_size: 32
- eval_batch_size: 1
- seed: 42
- 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 |
|---|---|---|---|---|
| 2.9556 | 15.62 | 500 | 2.9300 | 1.0 |
| 1.7874 | 31.25 | 1000 | 0.7566 | 0.6509 |
| 1.0131 | 46.88 | 1500 | 0.3671 | 0.3828 |
| 0.8439 | 62.5 | 2000 | 0.3350 | 0.3416 |
| 0.7502 | 78.12 | 2500 | 0.3155 | 0.3296 |
| 0.7093 | 93.75 | 3000 | 0.3182 | 0.3186 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
