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: 0.2315
- Wer: 13.2075
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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7229 | 5.0 | 250 | 0.8173 | 56.7933 |
| 0.2324 | 10.0 | 500 | 0.8472 | 50.4318 |
| 0.0673 | 15.0 | 750 | 0.9745 | 49.5250 |
| 0.0297 | 20.0 | 1000 | 1.0408 | 49.4675 |
| 0.0245 | 25.0 | 1250 | 0.2170 | 13.1495 |
| 0.0088 | 30.0 | 1500 | 0.2295 | 13.7591 |
| 0.0025 | 35.0 | 1750 | 0.2324 | 13.9478 |
| 0.0019 | 40.0 | 2000 | 0.2315 | 13.2075 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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Base model
openai/whisper-tiny