inctraining4 / README.md
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metadata
language:
  - sw
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_15_0
metrics:
  - wer
model-index:
  - name: Incremental Swahili Luganda
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Mix data
          type: mozilla-foundation/common_voice_15_0
          config: lg
          split: validation
          args: 'config: lu, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 30.713561255969235

Incremental Swahili Luganda

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

  • Loss: 0.3391
  • Wer: 30.7136

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
0.1672 0.0998 500 0.3706 33.9074
0.172 0.1996 1000 0.3714 33.9803
0.2094 0.2995 1500 0.3640 33.2407
0.1927 0.3993 2000 0.3577 32.5233
0.1905 0.4991 2500 0.3521 31.8810
0.1735 0.5989 3000 0.3470 31.3189
0.157 0.6987 3500 0.3428 31.0052
0.1784 0.7986 4000 0.3391 30.7136

Framework versions

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