---
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