metadata

library_name: transformers
language:
  - ar
license: apache-2.0
base_model: openai/whisper-small
tags:
  - generated_from_trainer
datasets:
  - raghadalghonaim/tts_arabic
metrics:
  - wer
model-index:
  - name: whisper_small_ar_ralghonaim
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: My Own Arabic DS
          type: raghadalghonaim/tts_arabic
          config: default
          split: None
          args: 'config: ar, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 42.69371737440302

whisper_small_ar_ralghonaim

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

Loss: 0.5957
Wer: 42.6937

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
0.6446	0.9268	1000	0.6416	48.7542
0.4115	1.8536	2000	0.5765	44.4449
0.2475	2.7804	3000	0.5745	43.3860
0.1478	3.7071	4000	0.5957	42.6937

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1