Whisper Medium en
This model is a fine-tuned version of openai/whisper-base on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.5062
- Wer: 19.8143
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: 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 |
|---|---|---|---|---|
| 0.3654 | 1.0974 | 1000 | 0.5075 | 20.6605 |
| 0.2314 | 3.0922 | 2000 | 0.5117 | 20.1370 |
| 0.261 | 5.087 | 3000 | 0.5058 | 20.1230 |
| 0.1793 | 7.0818 | 4000 | 0.5196 | 20.5831 |
| 0.2344 | 9.0766 | 5000 | 0.5062 | 19.8143 |
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-base-en-cv17
Base model
openai/whisper-baseDataset used to train deepdml/whisper-base-en-cv17
Evaluation results
- Wer on Common Voice 17.0test set self-reported19.814
- WER on google/fleurstest set self-reported14.000
- WER on facebook/voxpopulitest set self-reported13.250