metadata

library_name: transformers
language:
  - ar
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_17_0
metrics:
  - wer
model-index:
  - name: Whisper_Small_Ar500d
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common Voice 17.0 Arabic
          type: mozilla-foundation/common_voice_17_0
          config: ar
          split: validation
          args: 'config: ar, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 23.472893495603564

Whisper_Small_Ar500d

This model is a fine-tuned version of openai/whisper-small on the Common Voice 17.0 Arabic dataset. It achieves the following results on the evaluation set:

Loss: 0.2154
Wer Ortho: 40.5973
Wer: 23.4729

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: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant_with_warmup
lr_scheduler_warmup_steps: 50
training_steps: 500
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer Ortho	Wer
0.2544	0.6002	500	0.2154	40.5973	23.4729

Framework versions

Transformers 4.45.2
Pytorch 2.5.1+cu121
Datasets 3.2.0
Tokenizers 0.20.3