| --- |
| 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: 0.3160 |
| - Precision: 0.6783 |
| - Recall: 0.5978 |
| - F1: 0.6355 |
| - Accuracy: 0.9378 |
| - Matthews Correlation: 0.6031 |
|
|
| ## 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 | 1123.2456 | 0.0907 | 1.0 | 0.1663 | 0.0909 | 0.0045 | |
| | 0.1943 | 1.0 | 9050 | 0.1832 | 0.7346 | 0.2615 | 0.3857 | 0.9245 | 0.4096 | |
| | 0.1500 | 2.0 | 18100 | 0.1551 | 0.7019 | 0.4967 | 0.5817 | 0.9352 | 0.5574 | |
| | 0.1242 | 3.0 | 27150 | 0.1481 | 0.7381 | 0.5451 | 0.6271 | 0.9412 | 0.6040 | |
| | 0.1017 | 4.0 | 36200 | 0.1482 | 0.7413 | 0.5604 | 0.6383 | 0.9424 | 0.6147 | |
| | 0.0774 | 5.0 | 45250 | 0.1564 | 0.7179 | 0.6154 | 0.6627 | 0.9432 | 0.6342 | |
| | 0.0610 | 6.0 | 54300 | 0.1859 | 0.7579 | 0.5297 | 0.6235 | 0.9420 | 0.6044 | |
| | 0.0434 | 7.0 | 63350 | 0.2016 | 0.6754 | 0.6264 | 0.6499 | 0.9388 | 0.6170 | |
| | 0.0298 | 8.0 | 72400 | 0.2480 | 0.6520 | 0.6505 | 0.6513 | 0.9368 | 0.6165 | |
| | 0.0216 | 9.0 | 81450 | 0.2961 | 0.6819 | 0.5890 | 0.6321 | 0.9378 | 0.6002 | |
| | 0.0174 | 10.0 | 90500 | 0.3160 | 0.6783 | 0.5978 | 0.6355 | 0.9378 | 0.6031 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 5.3.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.5.0 |
| - Tokenizers 0.22.2 |
|
|
