Whisper Tiny En - ScienceTechnology - AI Concepts
This model is a fine-tuned version of openai/whisper-tiny on the fineaudio-ScienceTechnology-AI Concepts dataset. It achieves the following results on the evaluation set:
- Loss: 0.5842
- Wer: 32.0808
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.522 | 1.2690 | 1000 | 0.6057 | 37.2097 |
| 0.3557 | 2.5381 | 2000 | 0.5705 | 31.0737 |
| 0.2384 | 3.8071 | 3000 | 0.5771 | 31.5585 |
| 0.2008 | 5.0761 | 4000 | 0.5842 | 32.0808 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.4.0
- Datasets 3.1.0
- Tokenizers 0.20.0
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Base model
openai/whisper-tinyEvaluation results
- Wer on fineaudio-ScienceTechnology-AI Conceptsself-reported32.081