whisper-tiny-hausa3 / README.md
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metadata
library_name: transformers
language:
  - ha
license: apache-2.0
base_model: EYEDOL/whisper-tiny-hausa2
tags:
  - generated_from_trainer
datasets:
  - EYEDOL/naija-voices-hausa-split_0-6
metrics:
  - wer
model-index:
  - name: EYEDOL/whisper-tiny-hausa3
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: EYEDOL/naija-voices-hausa-split_0-6
          type: EYEDOL/naija-voices-hausa-split_0-6
        metrics:
          - name: Wer
            type: wer
            value: 0.43485342019543977

EYEDOL/whisper-tiny-hausa3

This model is a fine-tuned version of EYEDOL/whisper-tiny-hausa2 on the EYEDOL/naija-voices-hausa-split_0-6 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6238
  • Wer Ortho: 0.5015
  • Wer: 0.4349

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 OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: constant_with_warmup
  • lr_scheduler_warmup_steps: 0.1
  • num_epochs: 3
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Ortho Wer
1.2512 1.0 665 0.6263 0.5023 0.4362
1.1143 2.0 1330 0.6204 0.4940 0.4280
1.0009 3.0 1995 0.6238 0.5015 0.4349

Framework versions

  • Transformers 5.0.0
  • Pytorch 2.10.0+cu128
  • Datasets 4.8.3
  • Tokenizers 0.22.2