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End of training
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metadata
language:
  - ar
license: apache-2.0
base_model: openai/whisper-large-v3
tags:
  - whisper-event
  - generated_from_trainer
datasets:
  - mozilla-foundation/common_voice_11_0
metrics:
  - wer
model-index:
  - name: "Whisper whisper-large-v3\t ar1 - Mohamed Shaaban"
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: Common standard ar Voice 11.0
          type: mozilla-foundation/common_voice_11_0
        metrics:
          - name: Wer
            type: wer
            value: 0

Whisper whisper-large-v3 ar1 - Mohamed Shaaban

This model is a fine-tuned version of openai/whisper-large-v3 on the Common standard ar Voice 11.0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.4220
  • Wer: 0.0

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: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • 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: 1
  • num_epochs: 5

Training results

Training Loss Epoch Step Validation Loss Wer
0.5721 1.0 1 2.1602 100.0
0.5723 2.0 2 1.0610 33.3333
0.1861 3.0 3 0.6003 33.3333
0.0478 4.0 4 0.4661 0.0
0.0262 5.0 5 0.4220 0.0

Framework versions

  • Transformers 4.39.3
  • Pytorch 2.2.2
  • Datasets 2.18.0
  • Tokenizers 0.15.2