Whisper small shona
This model is a fine-tuned version of openai/whisper-small on the google/fleurs sn_zw dataset. It achieves the following results on the evaluation set:
- Loss: 1.1220
- Wer: 49.9096
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: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- total_eval_batch_size: 48
- 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 |
|---|---|---|---|---|
| 0.0064 | 24.24 | 400 | 0.9630 | 50.7233 |
| 0.001 | 48.48 | 800 | 1.0617 | 49.9397 |
| 0.0005 | 72.73 | 1200 | 1.1016 | 49.9397 |
| 0.0004 | 96.97 | 1600 | 1.1220 | 49.9096 |
| 0.0003 | 121.21 | 2000 | 1.1298 | 50.0422 |
Framework versions
- Transformers 4.37.1
- Pytorch 1.12.0+cu102
- Datasets 2.16.1
- Tokenizers 0.15.1