Whisper_large_Shona
This model is a fine-tuned version of openai/whisper-large-v2 on the google/fleurs sn_zw dataset. It achieves the following results on the evaluation set:
- Loss: 0.9189
- Wer: 37.5
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: 100
- training_steps: 1000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0005 | 41.64 | 500 | 0.8784 | 37.525 |
| 0.0003 | 83.32 | 1000 | 0.9189 | 37.5 |
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 realtime-speech/shona-finetune
Evaluation results
- Wer on google/fleurs sn_zwtest set self-reported37.500