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  ---
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- library_name: transformers
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- tags: []
 
 
 
 
 
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  ---
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- # Model Card for Model ID
 
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- ## Model Details
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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- ## How to Get Started with the Model
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- [More Information Needed]
 
1
  ---
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+ license: apache-2.0
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+ base_model: NbAiLab/nb-whisper-small-verbatim
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: nb-whisper-small-karelian-CodeSwitching
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+ results: []
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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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+ # nb-whisper-small-karelian-CodeSwitching
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+ This model is a fine-tuned version of [NbAiLab/nb-whisper-small-verbatim](https://huggingface.co/NbAiLab/nb-whisper-small-verbatim) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - eval_loss: 55.25
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+ - eval_wer: 1.0
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+ - eval_cer: 11.0447
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+ - eval_runtime: 86.5964
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+ - eval_samples_per_second: 4.966
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+ - eval_steps_per_second: 0.162
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+ - epoch: 0.4535
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+ - step: 100
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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: 0.007
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+ - train_batch_size: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - gradient_accumulation_steps: 2
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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: 1000
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+ - mixed_precision_training: Native AMP
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+ ### Framework versions
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+ - Transformers 4.41.2
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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