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README.md ADDED
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+ ---
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+ language:
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+ - tr
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+ license: apache-2.0
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+ base_model: openai/whisper-large-v2
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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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+ - mozilla-foundation/common_voice_13
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: 'Whisper Large v2 TR '
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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: Common Voice 13
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+ type: mozilla-foundation/common_voice_13
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+ config: tr
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+ split: None
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+ args: tr
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 11.477761836441895
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+ ---
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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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+
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+ # Whisper Large v2 TR
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+
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+ This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 13 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2089
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+ - Wer: 11.4778
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: constant_with_warmup
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+ - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 3
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|
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+ | 0.1641 | 1.0 | 3147 | 0.1899 | 11.9306 |
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+ | 0.0904 | 2.0 | 6294 | 0.1904 | 11.3074 |
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+ | 0.0547 | 3.0 | 9441 | 0.2089 | 11.4778 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.1
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+ - Pytorch 2.2.0+cu121
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+ - Datasets 2.17.0
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+ - Tokenizers 0.15.2
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