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--- |
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language: |
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- ar |
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license: apache-2.0 |
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base_model: openai/whisper-large-v3 |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- ahishamm/whisperQURANIC |
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metrics: |
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- wer |
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model-index: |
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- name: QURANIC Whisper Large V3 |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: whisperQURANIC |
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type: ahishamm/whisperQURANIC |
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args: 'config: ar, split: train' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 268.8141178069162 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# QURANIC Whisper Large V3 |
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This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the whisperQURANIC dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0238 |
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- Wer: 268.8141 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 1 |
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- training_steps: 2000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| 0.1467 | 0.4 | 200 | 0.1302 | 42.9071 | |
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| 0.1226 | 0.8 | 400 | 0.0958 | 156.6683 | |
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| 0.0746 | 1.2 | 600 | 0.0772 | 494.4510 | |
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| 0.0868 | 1.6 | 800 | 0.0678 | 252.8552 | |
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| 0.0801 | 2.0 | 1000 | 0.0560 | 361.0673 | |
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| 0.0552 | 2.4 | 1200 | 0.0473 | 153.8658 | |
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| 0.053 | 2.8 | 1400 | 0.0399 | 310.5204 | |
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| 0.0421 | 3.2 | 1600 | 0.0308 | 305.3961 | |
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| 0.0291 | 3.6 | 1800 | 0.0266 | 242.5182 | |
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| 0.0303 | 4.0 | 2000 | 0.0238 | 268.8141 | |
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### Framework versions |
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- Transformers 4.39.2 |
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- Pytorch 2.2.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.1 |
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