inctraining2 / 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: 33.5492118497232

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: 0.3560
  • Wer: 33.5492

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
0.2725 0.0810 500 0.4085 38.8803
0.2921 0.1620 1000 0.4086 37.8608
0.2746 0.2431 1500 0.3969 37.2596
0.2761 0.3241 2000 0.3825 36.0743
0.2799 0.4051 2500 0.3743 35.2544
0.2426 0.4861 3000 0.3672 34.4208
0.267 0.5671 3500 0.3589 33.7573
0.276 0.6481 4000 0.3560 33.5492

Framework versions

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