README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - afrispeech-200
metrics:
  - wer
model-index:
  - name: whisper-medium-23
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: afrispeech-200
          type: afrispeech-200
          config: all
          split: train
          args: all
        metrics:
          - name: Wer
            type: wer
            value: 0.562546896773502

whisper-medium-23

This model is a fine-tuned version of saif-daoud/whisper-medium-22 on the afrispeech-200 dataset. It achieves the following results on the evaluation set:

• Loss: 0.4774
• Wer: 0.5625

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-06
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 500
• training_steps: 750
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.8977	0.5	375	0.6403	0.1715
0.6345	1.5	750	0.4774	0.5625

Framework versions

• Transformers 4.28.0.dev0
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3