README.md

metadata

library_name: transformers
language:
  - ar
license: apache-2.0
base_model: openai/whisper-tiny
tags:
  - generated_from_trainer
datasets:
  - whitefox123/tashkeel
metrics:
  - wer
model-index:
  - name: Whisper Tiny Ar - AzeemX
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Tashkeel
          type: whitefox123/tashkeel
          config: default
          split: None
          args: 'config: ar, split: test'
        metrics:
          - name: Wer
            type: wer
            value: 40

Whisper Tiny Ar - AzeemX

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

• Loss: 0.2374
• Wer: 40.0

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: 5000
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2521	1.6	1000	0.3009	53.0811
0.146	3.2	2000	0.2476	42.5946
0.1238	4.8	3000	0.2334	40.1081
0.0916	6.4	4000	0.2372	39.5315
0.0866	8.0	5000	0.2374	40.0

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.1+cu121
• Datasets 3.0.1
• Tokenizers 0.20.0