Whisper Medium pt
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.2757
- Wer: 6.9248
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: 32
- 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
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1211 | 1.0173 | 1000 | 0.2010 | 7.8295 |
0.0393 | 2.0346 | 2000 | 0.2084 | 7.3020 |
0.0167 | 3.0519 | 3000 | 0.2243 | 7.0191 |
0.0049 | 4.0692 | 4000 | 0.2530 | 6.9807 |
0.0018 | 5.0865 | 5000 | 0.2757 | 6.9248 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
openai/whisper-mediumDataset used to train deepdml/whisper-medium-pt-cv17
Evaluation results
- Wer on Common Voice 17.0test set self-reported6.925
- WER on google/fleurstest set self-reported8.110
- WER on facebook/multilingual_librispeechtest set self-reported9.660