gha-whisper-small-twi-v3
This model is a fine-tuned version of teckedd/whisper-small-waxal-round2-specaug-v1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2959
- Wer: 0.2807
- Cer: 0.0958
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 1500
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.4513 | 0.4747 | 150 | 0.4382 | 0.3044 | 0.1058 |
| 0.308 | 0.9494 | 300 | 0.3023 | 0.2897 | 0.0975 |
| 0.2678 | 1.4241 | 450 | 0.2996 | 0.2969 | 0.1042 |
| 0.2636 | 1.8987 | 600 | 0.2959 | 0.2807 | 0.0958 |
| 0.2081 | 2.3734 | 750 | 0.2998 | 0.2896 | 0.0994 |
| 0.2006 | 2.8481 | 900 | 0.2989 | 0.2932 | 0.1012 |
| 0.1614 | 3.3228 | 1050 | 0.3043 | 0.3010 | 0.1050 |
| 0.169 | 3.7975 | 1200 | 0.3035 | 0.2906 | 0.1009 |
| 0.152 | 4.2722 | 1350 | 0.3090 | 0.3004 | 0.1065 |
| 0.1512 | 4.7468 | 1500 | 0.3084 | 0.2984 | 0.1034 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3