Whisper small Persian
This model is a fine-tuned version of openai/whisper-small on the mozilla-foundation/common_voice_11_0 fa dataset. It achieves the following results on the evaluation set:
- Loss: 0.4924
- Wer: 32.8995
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-06
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_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 |
---|---|---|---|---|
0.5533 | 1.56 | 500 | 0.7044 | 54.5499 |
0.3951 | 3.12 | 1000 | 0.5893 | 47.5210 |
0.3296 | 4.67 | 1500 | 0.5429 | 42.6451 |
0.2662 | 6.23 | 2000 | 0.5223 | 40.6644 |
0.2535 | 7.79 | 2500 | 0.5045 | 38.5304 |
0.224 | 9.35 | 3000 | 0.5002 | 36.8822 |
0.2204 | 10.9 | 3500 | 0.4967 | 35.3076 |
0.2024 | 12.46 | 4000 | 0.4951 | 34.9883 |
0.2099 | 14.02 | 4500 | 0.4921 | 34.9842 |
0.1836 | 15.58 | 5000 | 0.4924 | 34.8995 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
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Dataset used to train steja/whisper-small-persian
Evaluation results
- Wer on mozilla-foundation/common_voice_11_0 fatest set self-reported32.900