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README.md ADDED
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+ ---
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+ language:
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+ - pl
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+ license: apache-2.0
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+ base_model: openai/whisper-small
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - mozilla-foundation/common_voice_11_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Whisper small pl - Michel Mesquita
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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 11.0
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+ type: mozilla-foundation/common_voice_11_0
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+ config: pl
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+ split: None
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+ args: 'config: pl, split: test'
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 24.85216766310562
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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 small pl - Michel Mesquita
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+
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+ This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4764
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+ - Wer: 24.8522
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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: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 64
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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: 500
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+ - training_steps: 4000
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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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+ | 0.0854 | 2.5757 | 1000 | 0.3000 | 24.1906 |
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+ | 0.0137 | 5.1513 | 2000 | 0.3835 | 24.5255 |
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+ | 0.0039 | 7.7270 | 3000 | 0.4406 | 24.6676 |
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+ | 0.0023 | 10.3026 | 4000 | 0.4764 | 24.8522 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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