Whisper small mixed-English
This model is a fine-tuned version of openai/whisper-small on the "en" datasets:
- mozilla-foundation/common_voice_17_0
- google/fleurs
- facebook/voxpopuli
It achieves the following results on the evaluation set:
- Loss: 0.3741
- Wer: 13.5791
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: 64
- eval_batch_size: 16
- 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 |
---|---|---|---|---|
0.2018 | 0.2 | 1000 | 0.3925 | 14.4841 |
0.1553 | 0.4 | 2000 | 0.3887 | 14.0259 |
0.1545 | 0.6 | 3000 | 0.3805 | 14.0316 |
0.1223 | 0.8 | 4000 | 0.3776 | 13.6450 |
0.131 | 1.0 | 5000 | 0.3741 | 13.5791 |
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-smallDatasets used to train deepdml/whisper-small-mix-en
Evaluation results
- Wer on Common Voice 17.0test set self-reported13.579
- WER on google/fleurstest set self-reported7.320
- WER on facebook/voxpopulitest set self-reported7.060