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wav2vec2-vorarlbergerisch
This model is a fine-tuned version of facebook/wav2vec2-base-960h on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9241
- Wer: 0.4358
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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 62
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
12.6837 | 3.83 | 100 | 3.7188 | 1.0 |
3.33 | 7.68 | 200 | 3.0620 | 1.0 |
2.9508 | 11.53 | 300 | 2.5915 | 1.0101 |
1.8954 | 15.38 | 400 | 1.6930 | 0.8243 |
1.231 | 19.23 | 500 | 1.7179 | 0.7551 |
0.9862 | 23.08 | 600 | 1.5237 | 0.6529 |
0.7353 | 26.91 | 700 | 1.5119 | 0.5921 |
0.5368 | 30.75 | 800 | 1.5011 | 0.5574 |
0.4448 | 34.6 | 900 | 1.5334 | 0.5363 |
0.3278 | 38.45 | 1000 | 1.7125 | 0.5144 |
0.2575 | 42.3 | 1100 | 1.6529 | 0.4958 |
0.1966 | 46.15 | 1200 | 1.7670 | 0.4848 |
0.1552 | 49.98 | 1300 | 1.7586 | 0.4620 |
0.1118 | 53.83 | 1400 | 1.7912 | 0.4417 |
0.0847 | 57.68 | 1500 | 1.8709 | 0.4443 |
0.0654 | 61.53 | 1600 | 1.9241 | 0.4358 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3
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