Whisper Large V2 Malayalam
This model is a fine-tuned version of openai/whisper-large-v2 on the ICFOSS Malayalam Speech Corpus dataset. It achieves the following results on the evaluation set:
- Loss: 0.0617
- Wer: 44.1379
- Cer: 9.6895
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: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 0.1071 | 0.13 | 500 | 0.1274 | 62.9885 | 15.0225 |
| 0.0693 | 0.26 | 1000 | 0.1052 | 57.4713 | 13.0696 |
| 0.054 | 0.39 | 1500 | 0.0902 | 48.0460 | 11.5173 |
| 0.0494 | 0.51 | 2000 | 0.0774 | 46.4368 | 10.7912 |
| 0.0446 | 0.64 | 2500 | 0.0722 | 46.8966 | 10.7161 |
| 0.0463 | 0.77 | 3000 | 0.0699 | 46.2069 | 10.3405 |
| 0.0347 | 0.9 | 3500 | 0.0662 | 43.6782 | 10.2404 |
| 0.0233 | 1.03 | 4000 | 0.0688 | 45.7471 | 10.4407 |
| 0.0226 | 1.16 | 4500 | 0.0642 | 44.5977 | 10.1152 |
| 0.0194 | 1.28 | 5000 | 0.0617 | 44.1379 | 9.6895 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2