whisper-tiny-akan
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: 1.0747
- Wer: 43.6101
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: 0.0001
- 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: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4857 | 10.0 | 250 | 0.7120 | 57.1555 |
| 0.0806 | 20.0 | 500 | 0.8478 | 49.9411 |
| 0.0347 | 30.0 | 750 | 0.9223 | 48.1743 |
| 0.0168 | 40.0 | 1000 | 1.0079 | 55.1826 |
| 0.0085 | 50.0 | 1250 | 1.0402 | 47.3498 |
| 0.0051 | 60.0 | 1500 | 1.0890 | 46.7314 |
| 0.0029 | 70.0 | 1750 | 1.0639 | 44.9352 |
| 0.002 | 80.0 | 2000 | 1.0707 | 44.6702 |
| 0.0005 | 90.0 | 2250 | 1.0705 | 43.7574 |
| 0.0005 | 100.0 | 2500 | 1.0721 | 44.4052 |
| 0.0002 | 110.0 | 2750 | 1.0730 | 43.3451 |
| 0.0003 | 120.0 | 3000 | 1.0747 | 43.6101 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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Base model
openai/whisper-tiny