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End of training
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README.md
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---
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base_model: openai/whisper-large-v3
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datasets:
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- MightyStudent/Egyptian-ASR-MGB-3
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language:
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- ar
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library_name: peft
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license: apache-2.0
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metrics:
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- wer
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tags:
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- generated_from_trainer
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model-index:
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- name: Whisper large V3 Arabic
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results:
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- task:
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type: automatic-speech-recognition
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name: Automatic Speech Recognition
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dataset:
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name: MightyStudent/Egyptian-ASR-MGB-3
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type: MightyStudent/Egyptian-ASR-MGB-3
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metrics:
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- type: wer
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value: 38.095238095238095
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name: Wer
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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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# Whisper large V3 Arabic
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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 MightyStudent/Egyptian-ASR-MGB-3 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6890
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- Wer: 38.0952
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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: 2
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- eval_batch_size: 2
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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: 5
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- num_epochs: 1
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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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| 0.6852 | 0.2 | 10 | 0.7062 | 45.7143 |
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| 0.7504 | 0.4 | 20 | 0.6994 | 45.7143 |
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| 0.7219 | 0.6 | 30 | 0.6940 | 45.7143 |
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| 0.6971 | 0.8 | 40 | 0.6905 | 45.7143 |
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| 0.6846 | 1.0 | 50 | 0.6890 | 38.0952 |
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### Framework versions
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- PEFT 0.12.0
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- Transformers 4.44.2
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- Pytorch 2.4.0+cu121
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- Datasets 3.0.0
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- Tokenizers 0.19.1
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