metadata

language:
  - ar
license: apache-2.0
tags:
  - hf-asr-leaderboard
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: Whisper Small Ar - Abdallah Elbohy
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 11.0
          type: mozilla-foundation/common_voice_11_0
          config: ar
          split: test
          args: 'config: ar, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 49.80809842989625

Whisper Small Ar - Abdallah Elbohy

This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset For short transcription 30s but for long transcription it has some limitations and challenges. It achieves the following results on the evaluation set:

Loss: 0.3791
Wer: 49.8081

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: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0972	0.57	1000	0.3791	49.8081
0.0978	1.14	2000	0.3791	49.8081
0.0986	1.71	3000	0.3791	49.8081
0.1055	2.28	4000	0.3791	49.8081

Framework versions

Transformers 4.26.0.dev0
Pytorch 1.13.0+cu116
Datasets 2.8.0
Tokenizers 0.13.2