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Whisper_small_Somali
This model is a fine-tuned version of openai/whisper-small on the google/fleurs so_so dataset. It achieves the following results on the evaluation set:
- Loss: 2.0764
- Wer: 66.5950
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: 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: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0205 | 30.74 | 400 | 1.8418 | 67.2524 |
| 0.0012 | 61.52 | 800 | 2.0764 | 66.5950 |
| 0.0006 | 92.3 | 1200 | 2.1537 | 67.6452 |
| 0.0004 | 123.07 | 1600 | 2.1930 | 67.1367 |
| 0.0004 | 153.81 | 2000 | 2.2065 | 66.9299 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.13.2
