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whisper-tiny-fluers_V2_telugu_Augmentation_full_datset_V2_e5
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: 0.3374
- Wer: 61.2000
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: 1.5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-06
- 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 |
|---|---|---|---|---|
| 1.2926 | 0.09 | 300 | 1.3993 | 129.5 |
| 1.0948 | 0.18 | 600 | 1.2674 | 109.1500 |
| 0.6591 | 0.28 | 900 | 0.5519 | 81.55 |
| 0.5326 | 0.37 | 1200 | 0.4361 | 72.55 |
| 0.4737 | 0.46 | 1500 | 0.4036 | 69.2000 |
| 0.4239 | 0.55 | 1800 | 0.3793 | 63.6 |
| 0.4011 | 0.64 | 2100 | 0.3625 | 62.2500 |
| 0.3687 | 0.73 | 2400 | 0.3651 | 62.5 |
| 0.3712 | 0.83 | 2700 | 0.3491 | 59.9 |
| 0.3686 | 0.92 | 3000 | 0.3438 | 60.6500 |
| 0.3381 | 1.01 | 3300 | 0.3391 | 58.25 |
| 0.3483 | 1.1 | 3600 | 0.3385 | 60.0500 |
| 0.341 | 1.19 | 3900 | 0.3374 | 61.2000 |
Framework versions
- Transformers 4.28.0.dev0
- Pytorch 1.12.1
- Datasets 2.11.0
- Tokenizers 0.13.3
