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This model was trained from scratch on the librispeech_asr dataset. It achieves the following results on the evaluation set:
- Loss: 0.9599
- Wer: 0.1442
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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 1000
- num_epochs: 20.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
6.1431 | 1.68 | 1500 | 6.0870 | 1.4277 |
5.498 | 3.36 | 3000 | 5.5505 | 1.6318 |
3.575 | 5.04 | 4500 | 3.7856 | 0.6683 |
1.7532 | 6.73 | 6000 | 2.4603 | 0.3576 |
1.6379 | 8.41 | 7500 | 1.8847 | 0.2932 |
1.3145 | 10.09 | 9000 | 1.5027 | 0.2222 |
0.8389 | 11.77 | 10500 | 1.2637 | 0.1855 |
0.9239 | 13.45 | 12000 | 1.1424 | 0.1683 |
0.6666 | 15.13 | 13500 | 1.0562 | 0.1593 |
0.5258 | 16.82 | 15000 | 0.9911 | 0.1489 |
0.4733 | 18.5 | 16500 | 0.9599 | 0.1442 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.3
- Tokenizers 0.11.0
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