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whisper-small-ar_20_02_Suite
This model is a fine-tuned version of openai/whisper-small on common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.2310
- Wer: 20.5386
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 6000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.2646 | 0.39 | 1000 | 0.2858 | 25.7695 |
| 0.2052 | 0.78 | 2000 | 0.2467 | 22.6620 |
| 0.136 | 1.17 | 3000 | 0.2326 | 21.2877 |
| 0.1403 | 1.57 | 4000 | 0.2396 | 21.6093 |
| 0.1195 | 1.96 | 5000 | 0.2287 | 20.3640 |
| 0.0735 | 2.35 | 6000 | 0.2310 | 20.5386 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.12.0
- Datasets 2.1.0
- Tokenizers 0.12.1
