README.md

metadata

language:
  - ar
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - taqwa92/tm_data
metrics:
  - wer
base_model: openai/whisper-small
model-index:
  - name: Whisper Small Arabic- Taqwa
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: tm_data
          type: taqwa92/tm_data
          config: default
          split: test[:5%]
          args: 'config: ar, split: test'
        metrics:
          - type: wer
            value: 52.138728323699425
            name: Wer

Whisper Small Arabic- Taqwa

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

• Loss: 0.5471
• Wer: 52.1387

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: 16
• 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: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1628	5.0	500	0.5471	52.1387

Framework versions

• Transformers 4.29.0.dev0
• Pytorch 2.0.0+cu118
• Datasets 2.11.0
• Tokenizers 0.13.3