Whisper Medium it
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: 0.1462
- Wer: 5.7098
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 |
---|---|---|---|---|
0.1755 | 0.1730 | 1000 | 0.1974 | 8.0595 |
0.157 | 0.3461 | 2000 | 0.1776 | 7.1199 |
0.1287 | 0.5191 | 3000 | 0.1622 | 6.5201 |
0.1287 | 0.6922 | 4000 | 0.1521 | 5.9863 |
0.1168 | 0.8652 | 5000 | 0.1462 | 5.7098 |
Framework versions
- Transformers 4.42.0.dev0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for deepdml/whisper-medium-it-cv17
Base model
openai/whisper-mediumDataset used to train deepdml/whisper-medium-it-cv17
Evaluation results
- Wer on Common Voice 17.0test set self-reported5.710
- WER on google/fleurstest set self-reported4.470
- WER on facebook/multilingual_librispeechtest set self-reported17.250
- WER on facebook/voxpopulitest set self-reported18.750