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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 |
### Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2
|