Whisper small using Common Voice 16 (pt)
This model is a fine-tuned version of openai/whisper-small on the Mozilla Common Voices - 16.0 - Portuguese dataset. It achieves the following results on the evaluation set:
- Loss: 0.2712
- Wer: 17.3335
- Wer Normalized: 11.3321
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Wer Normalized |
---|---|---|---|---|---|
0.2591 | 0.37 | 500 | 0.2776 | 20.0727 | 13.6707 |
0.2626 | 0.74 | 1000 | 0.2599 | 19.4005 | 13.3337 |
0.1131 | 1.11 | 1500 | 0.2516 | 18.0414 | 12.1330 |
0.1016 | 1.48 | 2000 | 0.2482 | 18.3597 | 11.9244 |
0.1094 | 1.85 | 2500 | 0.2411 | 17.4192 | 11.6017 |
0.0524 | 2.22 | 3000 | 0.2512 | 17.3546 | 11.4637 |
0.0433 | 2.59 | 3500 | 0.2496 | 17.0895 | 11.2984 |
0.0453 | 2.96 | 4000 | 0.2479 | 17.0362 | 11.2679 |
0.0201 | 3.33 | 4500 | 0.2693 | 17.6632 | 11.7109 |
0.0229 | 3.7 | 5000 | 0.2712 | 17.3335 | 11.3321 |
Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.15.1
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Model tree for thiagobarbosa/whisper-small-common-voice-16-pt
Base model
openai/whisper-small
Finetuned
this model
Dataset used to train thiagobarbosa/whisper-small-common-voice-16-pt
Evaluation results
- Wer on Mozilla Common Voices - 16.0 - Portuguesetest set self-reported17.334