| --- |
| library_name: transformers |
| language: |
| - en |
| license: apache-2.0 |
| base_model: answerdotai/ModernBERT-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| - matthews_correlation |
| model-index: |
| - name: DisamBertCrossEncoder-base |
| 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. --> |
|
|
| # DisamBertCrossEncoder-base |
|
|
| 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: 0.9841 |
| - Precision: 0.6896 |
| - Recall: 0.6396 |
| - F1: 0.6636 |
| - Accuracy: 0.9412 |
| - Matthews Correlation: 0.6320 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - gradient_accumulation_steps: 5 |
| - total_train_batch_size: 320 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Matthews Correlation | |
| |:-------------:|:-----:|:------:|:---------------:|:---------:|:------:|:------:|:--------:|:--------------------:| |
| | No log | 0 | 0 | 430.2531 | 0.0905 | 0.9978 | 0.1660 | 0.0911 | -0.0157 | |
| | 0.0672 | 1.0 | 12551 | 0.1555 | 0.6786 | 0.5846 | 0.6281 | 0.9372 | 0.5960 | |
| | 0.0550 | 2.0 | 25102 | 0.1447 | 0.7176 | 0.6813 | 0.6990 | 0.9468 | 0.6701 | |
| | 0.0427 | 3.0 | 37653 | 0.1498 | 0.7690 | 0.6440 | 0.7010 | 0.9502 | 0.6772 | |
| | 0.0309 | 4.0 | 50204 | 0.1779 | 0.6773 | 0.7011 | 0.6890 | 0.9426 | 0.6575 | |
| | 0.0179 | 5.0 | 62755 | 0.2554 | 0.7021 | 0.6681 | 0.6847 | 0.9442 | 0.6543 | |
| | 0.0092 | 6.0 | 75306 | 0.3257 | 0.6927 | 0.6637 | 0.6779 | 0.9428 | 0.6467 | |
| | 0.0047 | 7.0 | 87857 | 0.4757 | 0.6674 | 0.6791 | 0.6732 | 0.9402 | 0.6403 | |
| | 0.0022 | 8.0 | 100408 | 0.6664 | 0.6943 | 0.6440 | 0.6682 | 0.9420 | 0.6370 | |
| | 0.0011 | 9.0 | 112959 | 0.8230 | 0.6872 | 0.6374 | 0.6613 | 0.9408 | 0.6295 | |
| | 0.0009 | 10.0 | 125510 | 0.9841 | 0.6896 | 0.6396 | 0.6636 | 0.9412 | 0.6320 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 5.3.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.5.0 |
| - Tokenizers 0.22.2 |
|
|
