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Whisper Small Luganda

This model is a fine-tuned version of openai/whisper-small on the Common Voice 15.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4482
  • Wer: 43.0651

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: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • 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
0.8094 0.0682 500 0.8624 73.2082
0.6104 0.1364 1000 0.6438 60.0304
0.5388 0.2045 1500 0.5586 51.9028
0.4618 0.2727 2000 0.5165 48.3825
0.4339 0.3409 2500 0.4886 46.0645
0.4229 0.4091 3000 0.4672 44.7809
0.3948 0.4772 3500 0.4544 43.5807
0.4017 0.5454 4000 0.4482 43.0651

Framework versions

  • Transformers 4.40.0
  • Pytorch 2.2.2+cu118
  • Datasets 2.19.0
  • Tokenizers 0.19.1
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Finetuned from

Dataset used to train mn720/inctraining

Evaluation results