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README.md
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---
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language:
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- ps_af
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license: apache-2.0
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tags:
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- whisper-event
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- generated_from_trainer
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datasets:
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- google/fleurs
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metrics:
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- wer
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model-index:
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- name: Whisper Small Pashto - Augmented
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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: google/fleurs
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type: google/fleurs
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config: null
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split: None
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metrics:
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- name: Wer
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type: wer
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value: 53.62439467312349
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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 Small Pashto - Augmented
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the google/fleurs dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6979
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- Wer: 53.6244
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- Cer: 22.6847
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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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- gradient_accumulation_steps: 16
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- total_train_batch_size: 32
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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: 30
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- training_steps: 300
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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 | Cer |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|
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| 0.9683 | 1.19 | 100 | 0.8812 | 139.3765 | 131.6166 |
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| 0.6848 | 2.38 | 200 | 0.7543 | 145.9973 | 151.3369 |
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| 0.5548 | 3.57 | 300 | 0.6979 | 53.6244 | 22.6847 |
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### Framework versions
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- Transformers 4.26.0.dev0
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- Pytorch 1.13.1+cu117
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- Datasets 2.8.1.dev0
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- Tokenizers 0.13.2
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