openai/whisper-tiny.en
This model is a fine-tuned version of openai/whisper-tiny.en on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6129
- Wer: 18.2504
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: 32
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.3898 | 4.02 | 1000 | 0.4541 | 17.0533 |
| 0.2333 | 8.04 | 2000 | 0.4818 | 16.6839 |
| 0.0899 | 13.01 | 3000 | 0.5512 | 17.3679 |
| 0.0368 | 17.02 | 4000 | 0.5962 | 17.6199 |
| 0.0289 | 21.04 | 5000 | 0.6129 | 18.2504 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.9.1.dev0
- Tokenizers 0.13.2
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Model tree for rishabhjain16/whisper_tiny_en_to_myst55h
Base model
openai/whisper-tiny.enEvaluation results
- WER on rishabhjain16/infer_pfstest set self-reported54.680
- WER on rishabhjain16/infer_mysttest set self-reported17.560
- WER on rishabhjain16/infer_cmutest set self-reported33.530
- WER on rishabhjain16/libritts_dev_cleantest set self-reported14.710