metadata

library_name: transformers
language:
  - ar
base_model: Ibrhm-S/arabic-speech-to-text
tags:
  - generated_from_trainer
datasets:
  - Ibrhm-S/arabic-speech-to-text
metrics:
  - wer
model-index:
  - name: Whisper Small Ar - Ibrhm S
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: arabic-speech-to-text
          type: Ibrhm-S/arabic-speech-to-text
          args: 'config: ar, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 96.58314350797266

Whisper Small Ar - Ibrhm S

This model is a fine-tuned version of Ibrhm-S/arabic-speech-to-text on the arabic-speech-to-text dataset. It achieves the following results on the evaluation set:

Loss: 3.1640
Wer: 96.5831

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: 5
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
0.0002	333.3333	1000	2.1972	94.9886
0.0001	666.6667	2000	2.7759	95.8998
0.0	1000.0	3000	3.0540	95.8998
0.0	1333.3333	4000	3.1640	96.5831

Framework versions

Transformers 4.45.0.dev0
Pytorch 2.3.1+cu121
Datasets 2.21.0
Tokenizers 0.19.1