whisper-tiny-am
This model is a fine-tuned version of openai/whisper-tiny on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2320
- Wer: 58.5201
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- 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 |
|---|---|---|---|---|
| 0.2711 | 1.4706 | 1000 | 0.3047 | 69.7082 |
| 0.1957 | 2.9412 | 2000 | 0.2488 | 63.4693 |
| 0.1385 | 4.4118 | 3000 | 0.2366 | 60.0677 |
| 0.1278 | 5.8824 | 4000 | 0.2320 | 58.5201 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for Gizachew/whisper-tiny-am
Base model
openai/whisper-tiny