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unanam/finetune_base

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README.md ADDED
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+ ---
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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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+ - generated_from_trainer
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+ model-index:
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+ - name: finetune_base
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+ results: []
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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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+ # finetune_base
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2932
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+ - Cer: 8.8686
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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: 5e-06
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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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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 16
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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 | Cer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|
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+ | 0.0863 | 2.76 | 1000 | 0.2303 | 9.1216 |
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+ | 0.0154 | 5.52 | 2000 | 0.2505 | 8.6437 |
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+ | 0.002 | 8.29 | 3000 | 0.2877 | 8.6297 |
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+ | 0.0021 | 11.05 | 4000 | 0.2932 | 8.8686 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.0.0
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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