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Whisper Tiny ml - Bharat Ramanathan
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: 1.1286
- Wer: 106.9296
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: 500
- training_steps: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.5755 | 4.02 | 500 | 0.4241 | 81.2652 |
| 0.4182 | 9.01 | 1000 | 0.3245 | 72.7494 |
| 0.3387 | 14.01 | 1500 | 0.2914 | 67.2749 |
| 0.2923 | 19.0 | 2000 | 0.2745 | 60.3406 |
| 0.2596 | 24.0 | 2500 | 0.2645 | 58.2725 |
| 0.2356 | 28.02 | 3000 | 0.2629 | 60.3406 |
| 0.2167 | 33.01 | 3500 | 0.2647 | 59.9757 |
| 0.2039 | 4.02 | 4000 | 0.2617 | 58.2725 |
| 0.1938 | 9.01 | 4500 | 0.2644 | 58.2725 |
| 0.1858 | 14.01 | 5000 | 0.2636 | 58.7591 |
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
