| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: answerdotai/ModernBERT-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - f1 |
| | - accuracy |
| | model-index: |
| | - name: valueeval24-modern-bert-cos-initialfreeze-diff-lr |
| | 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. --> |
| |
|
| | # valueeval24-modern-bert-cos-initialfreeze-diff-lr |
| |
|
| | This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.7684 |
| | - F1: 0.2039 |
| | - Roc Auc: 0.5705 |
| | - Accuracy: 0.1033 |
| |
|
| | ## Model description |
| |
|
| | More information needed |
| |
|
| | ## Intended uses & limitations |
| |
|
| | More information needed |
| |
|
| | ## Training and evaluation data |
| |
|
| | More information needed |
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 3e-05 |
| | - train_batch_size: 8 |
| | - eval_batch_size: 8 |
| | - seed: 42 |
| | - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_ratio: 0.1 |
| | - num_epochs: 20 |
| | - mixed_precision_training: Native AMP |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy | |
| | |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:| |
| | | 0.0167 | 1.0 | 3115 | 0.2207 | 0.2035 | 0.5691 | 0.1071 | |
| | | 0.0138 | 2.0 | 6230 | 0.2613 | 0.2091 | 0.5730 | 0.1083 | |
| | | 0.0102 | 3.0 | 9345 | 0.3444 | 0.2249 | 0.5841 | 0.1147 | |
| | | 0.0073 | 4.0 | 12460 | 0.6223 | 0.1944 | 0.5654 | 0.0991 | |
| | | 0.0053 | 5.0 | 15575 | 0.6920 | 0.1973 | 0.5668 | 0.1004 | |
| | | 0.0022 | 6.0 | 18690 | 0.7143 | 0.1983 | 0.5680 | 0.0996 | |
| | | 0.0012 | 7.0 | 21805 | 0.7309 | 0.1968 | 0.5672 | 0.0993 | |
| | | 0.0007 | 8.0 | 24920 | 0.7349 | 0.2035 | 0.5706 | 0.1031 | |
| | | 0.0006 | 9.0 | 28035 | 0.7521 | 0.2064 | 0.5718 | 0.1070 | |
| | | 0.0003 | 10.0 | 31150 | 0.7684 | 0.2039 | 0.5705 | 0.1033 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.53.1 |
| | - Pytorch 2.6.0+cu124 |
| | - Datasets 2.14.4 |
| | - Tokenizers 0.21.2 |
| | |
