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valueeval24-modern-bert-cos-initialfreeze-diff-lr-2

Text Classification
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modernbert
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README.md ADDED
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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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+ - f1
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+ - accuracy
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+ model-index:
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+ - name: valueeval24-modern-bert-cos-initialfreeze-diff-lr-2
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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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+ # valueeval24-modern-bert-cos-initialfreeze-diff-lr-2
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+
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+ This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7800
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+ - F1: 0.2007
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+ - Roc Auc: 0.5700
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+ - Accuracy: 0.1008
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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: 3e-05
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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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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: cosine
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+ - lr_scheduler_warmup_ratio: 0.5
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+ - num_epochs: 20
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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 | F1 | Roc Auc | Accuracy |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
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+ | 0.0167 | 1.0 | 3115 | 0.1945 | 0.1955 | 0.5655 | 0.1004 |
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+ | 0.0146 | 2.0 | 6230 | 0.2180 | 0.1987 | 0.5679 | 0.1013 |
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+ | 0.0133 | 3.0 | 9345 | 0.2485 | 0.2006 | 0.5698 | 0.0991 |
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+ | 0.0114 | 4.0 | 12460 | 0.2969 | 0.1893 | 0.5627 | 0.0950 |
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+ | 0.0101 | 5.0 | 15575 | 0.3334 | 0.1969 | 0.5684 | 0.0973 |
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+ | 0.0082 | 6.0 | 18690 | 0.4324 | 0.1971 | 0.5682 | 0.0995 |
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+ | 0.0065 | 7.0 | 21805 | 0.6038 | 0.1950 | 0.5677 | 0.0959 |
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+ | 0.0043 | 8.0 | 24920 | 0.6648 | 0.2028 | 0.5731 | 0.0978 |
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+ | 0.0033 | 9.0 | 28035 | 0.6840 | 0.2052 | 0.5725 | 0.1030 |
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+ | 0.0015 | 10.0 | 31150 | 0.7048 | 0.2037 | 0.5728 | 0.1016 |
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+ | 0.0009 | 11.0 | 34265 | 0.7291 | 0.1944 | 0.5667 | 0.0987 |
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+ | 0.0006 | 12.0 | 37380 | 0.7446 | 0.1990 | 0.5693 | 0.0993 |
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+ | 0.0004 | 13.0 | 40495 | 0.7531 | 0.2017 | 0.5712 | 0.1004 |
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+ | 0.0003 | 14.0 | 43610 | 0.7655 | 0.1987 | 0.5684 | 0.1008 |
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+ | 0.0002 | 15.0 | 46725 | 0.7750 | 0.1976 | 0.5680 | 0.0988 |
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+ | 0.0002 | 16.0 | 49840 | 0.7800 | 0.2007 | 0.5700 | 0.1008 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.53.1
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+ - Pytorch 2.6.0+cu124
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+ - Datasets 2.14.4
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+ - Tokenizers 0.21.2
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