Whisper Small it
This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.1960
- Wer: 8.6442
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 |
---|---|---|---|---|
0.2184 | 0.3460 | 1000 | 0.2458 | 11.3839 |
0.1863 | 0.6920 | 2000 | 0.2186 | 10.1784 |
0.1138 | 1.0381 | 3000 | 0.2049 | 9.1252 |
0.1184 | 1.3841 | 4000 | 0.1996 | 8.9385 |
0.1189 | 1.7301 | 5000 | 0.1960 | 8.6442 |
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-small-it-cv17
Base model
openai/whisper-smallDataset used to train deepdml/whisper-small-it-cv17
Evaluation results
- Wer on Common Voice 17.0test set self-reported8.644
- WER on google/fleurstest set self-reported6.690
- WER on facebook/multilingual_librispeechtest set self-reported19.400
- WER on facebook/voxpopulitest set self-reported22.610