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Whisper Tiny Ta - Bharat Ramanathan
This model is a fine-tuned version of openai/whisper-tiny on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3096
- Wer: 30.1027
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5622 | 0.2 | 1000 | 0.4460 | 41.4141 |
| 0.4151 | 0.4 | 2000 | 0.3657 | 35.1390 |
| 0.3727 | 0.6 | 3000 | 0.3417 | 33.1723 |
| 0.3519 | 0.8 | 4000 | 0.3252 | 31.9497 |
| 0.3354 | 1.0 | 5000 | 0.3192 | 31.3997 |
| 0.3492 | 0.1 | 6000 | 0.3283 | 31.6966 |
| 0.3229 | 0.2 | 7000 | 0.3211 | 31.1339 |
| 0.3193 | 0.3 | 8000 | 0.3138 | 30.5161 |
| 0.314 | 0.4 | 9000 | 0.3112 | 30.1832 |
| 0.3087 | 0.5 | 10000 | 0.3096 | 30.1027 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
