README.md

metadata

language:
  - ar
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - arab
metrics:
  - wer
base_model: openai/whisper-small
model-index:
  - name: Whisper Small ar - Atishay Sharma
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: arabic
          type: arab
          config: default
          split: train
          args: 'config: ar, split: test'
        metrics:
          - type: wer
            value: 4.545454545454546
            name: Wer

Whisper Small ar - Atishay Sharma

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

• Loss: 0.0922
• Wer: 4.5455

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: 8
• eval_batch_size: 4
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 16
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 10
• training_steps: 500
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.0	500.0	500	0.0922	4.5455

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2