Whisper Small Isizulu-Asr-0.9-Speed
This model is a fine-tuned version of openai/whisper-small on the ISIZULU-ASR-0.9-SPEED dataset. It achieves the following results on the evaluation set:
- eval_loss: 1.3053
- eval_wer: 58.5082
- eval_runtime: 23.1359
- eval_samples_per_second: 6.051
- eval_steps_per_second: 0.389
- step: 0
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: 32
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.2.0
- Tokenizers 0.22.1
- Downloads last month
- 39
Model tree for zionia/whisper-small-isizulu-0.9-speed
Base model
openai/whisper-small