Whisper Base Mnong
This model is a fine-tuned version of openai/whisper-base on the MnongAudio-v2 dataset. It achieves the following results on the evaluation set:
- Loss: 0.7309
- Wer: 78.4474
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 |
|---|---|---|---|---|
| 1.2709 | 2.0325 | 1000 | 1.3573 | 121.7936 |
| 0.5929 | 4.0650 | 2000 | 0.9105 | 81.5333 |
| 0.2907 | 6.0976 | 3000 | 0.7671 | 80.9065 |
| 0.204 | 8.1301 | 4000 | 0.7309 | 78.4474 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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