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README.md
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---
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license:
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- f1
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model-index:
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- name: roberta-base-ad-detector
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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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# roberta-base-ad-detector
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an
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It achieves the following results on the evaluation set:
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- Loss: 0.0010
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- Accuracy: 1.0
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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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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 1
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### Training results
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### Framework versions
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- Transformers 4.27.4
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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license: apache-2.0
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metrics:
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- accuracy
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- f1
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model-index:
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- name: roberta-base-ad-detector
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results: []
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datasets:
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- 0x7194633/ad_detector
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language:
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- en
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pipeline_tag: text-classification
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# roberta-base-ad-detector
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an [ad_detector](https://huggingface.co/0x7194633/ad_detector) dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0010
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- Accuracy: 1.0
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More information needed
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### Training hyperparameters
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The following hyperparameters were used during training:
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- num_epochs: 1
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