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metadata
library_name: transformers
language:
  - zu
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - zionia/isizulu-asr-1.1-speed
metrics:
  - wer
model-index:
  - name: Whisper Small Isizulu-Asr-1.1-Speed
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: ISIZULU-ASR-1.1-SPEED
          type: zionia/isizulu-asr-1.1-speed
          args: 'split: train+test'
        metrics:
          - name: Wer
            type: wer
            value: 53.6

Whisper Small Isizulu-Asr-1.1-Speed

This model is a fine-tuned version of openai/whisper-small on the ISIZULU-ASR-1.1-SPEED dataset. It achieves the following results on the evaluation set:

  • Loss: 1.3263
  • Wer: 53.6

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

Training results

Training Loss Epoch Step Validation Loss Wer
0.0004 55.5556 1000 1.2327 53.8286
0.0001 111.1111 2000 1.2957 53.8286
0.0001 166.6667 3000 1.3263 53.6
0.0001 222.2222 4000 1.3378 54.1714

Framework versions

  • Transformers 4.57.0
  • Pytorch 2.8.0+cu128
  • Datasets 4.2.0
  • Tokenizers 0.22.1