metadata

library_name: transformers
language:
  - ar
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - alexstokes/masri_audio_transcription
metrics:
  - wer
model-index:
  - name: Whisper Small - Egyptian Arabic
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Egyptian Arabic Speech Recognition
          type: alexstokes/masri_audio_transcription
          args: 'split: train'
        metrics:
          - name: Wer
            type: wer
            value: 41.667657904127516

Whisper Small - Egyptian Arabic

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

Loss: 0.9560
Wer: 41.6677

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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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
0.0518	7.6336	1000	0.7113	42.9166
0.004	15.2672	2000	0.8712	41.2157
0.001	22.9008	3000	0.9327	42.0245
0.0006	30.5344	4000	0.9560	41.6677

Framework versions

Transformers 4.46.3
Pytorch 2.4.1.post303
Datasets 3.1.0
Tokenizers 0.20.3