whisper-base-akan
This model is a fine-tuned version of openai/whisper-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.9478
- Wer: 40.9025
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 |
|---|---|---|---|---|
| 0.5893 | 10.0 | 500 | 0.7149 | 51.7322 |
| 0.0835 | 20.0 | 1000 | 0.8352 | 42.5328 |
| 0.0199 | 30.0 | 1500 | 0.9229 | 41.2373 |
| 0.0066 | 40.0 | 2000 | 0.9478 | 40.9025 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.2
- Tokenizers 0.20.1
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Base model
openai/whisper-base