| ---
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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
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| results: []
|
| ---
|
|
|
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| should probably proofread and complete it, then remove this comment. -->
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|
|
| # valueeval24-modern-bert
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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 an unknown dataset.
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| It achieves the following results on the evaluation set:
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| - Loss: 0.1613
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| - F1: 0.3178
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| - Roc Auc: 0.6190
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| - Accuracy: 0.1954
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|
|
| ## Model description
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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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| 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: 2024
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| - optimizer: Use 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: linear
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| - lr_scheduler_warmup_ratio: 0.01
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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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| | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
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| |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
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| | 0.1463 | 1.0 | 2883 | 0.1052 | 0.1633 | 0.5464 | 0.0854 |
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| | 0.1003 | 2.0 | 5766 | 0.0995 | 0.2146 | 0.5640 | 0.1188 |
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| | 0.0907 | 3.0 | 8649 | 0.0981 | 0.2777 | 0.5899 | 0.1662 |
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| | 0.0806 | 4.0 | 11532 | 0.1001 | 0.3038 | 0.6035 | 0.1804 |
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| | 0.0685 | 5.0 | 14415 | 0.1048 | 0.3099 | 0.6094 | 0.1914 |
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| | 0.0549 | 6.0 | 17298 | 0.1104 | 0.3209 | 0.6177 | 0.1968 |
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| | 0.0412 | 7.0 | 20181 | 0.1158 | 0.3197 | 0.6198 | 0.1934 |
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| | 0.0285 | 8.0 | 23064 | 0.1232 | 0.3226 | 0.6210 | 0.1974 |
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| | 0.0184 | 9.0 | 25947 | 0.1312 | 0.3157 | 0.6186 | 0.1943 |
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| | 0.0114 | 10.0 | 28830 | 0.1381 | 0.3176 | 0.6192 | 0.1951 |
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| | 0.0071 | 11.0 | 31713 | 0.1463 | 0.3216 | 0.6216 | 0.1972 |
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| | 0.0047 | 12.0 | 34596 | 0.1542 | 0.3153 | 0.6168 | 0.1959 |
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| | 0.0032 | 13.0 | 37479 | 0.1613 | 0.3178 | 0.6190 | 0.1954 |
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| ### Framework versions
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|
|
| - Transformers 4.53.0
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| - Pytorch 2.5.1+cu121
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| - Datasets 3.6.0
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| - Tokenizers 0.21.2
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| |
