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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: answerdotai/ModernBERT-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: edu-modernbert |
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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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# edu-modernbert |
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This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the [HuggingFaceFW/fineweb-edu-llama3-annotations](https://huggingface.co/datasets/HuggingFaceFW/fineweb-edu-llama3-annotations) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2453 |
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- Precision: 0.5901 |
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- Recall: 0.5245 |
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- F1: 0.5504 |
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- Accuracy: 0.7508 |
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- Binary Precision: 0.8168 |
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- Binary Recall: 0.6856 |
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- Binary F1: 0.7455 |
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- Binary Accuracy: 0.9578 |
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<div class="alert alert-info"> |
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<b>Note:</b> the binary classification score is calculated by thresholding at 3 i.e (0-2 -> 0, 3-5 -> 1). |
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</div> |
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In comparison the reproduced version of [HuggingFaceFW/fineweb-edu-classifier](https://huggingface.co/HuggingFaceFW/fineweb-edu-classifier) achieves: |
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- Loss: 0.2475 |
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- Precision: 0.5595 |
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- Recall: 0.4360 |
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- F1: 0.4704 |
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- Accuracy: 0.7123 |
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- Binary Precision: 0.7781 |
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- Binary Recall: 0.5566 |
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- Binary F1: 0.6490 |
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- Binary Accuracy: 0.9457 |
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<div class="alert alert-info"> |
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<b>Note:</b> one difference is that ModernBERT-base is fully trained while the original classifier trains only the regression head.. |
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</div> |
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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: 5e-05 |
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- train_batch_size: 256 |
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- eval_batch_size: 256 |
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- seed: 0 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20(totally not needed, 3 epochs already achieve great results) |
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### Framework versions |
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- Transformers 4.48.0.dev0 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
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