---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
model-index:
- name: binary_paragraph
  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. -->

# binary_paragraph

This model is a fine-tuned version of [answerdotai/ModernBERT-large](https://huggingface.co/answerdotai/ModernBERT-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2290
- Classification Report: {'0': {'precision': 0.9048991354466859, 'recall': 0.9861809045226131, 'f1-score': 0.9437932070934776, 'support': 1592.0}, '1': {'precision': 0.811965811965812, 'recall': 0.36538461538461536, 'f1-score': 0.5039787798408488, 'support': 260.0}, 'accuracy': 0.8990280777537797, 'macro avg': {'precision': 0.858432473706249, 'recall': 0.6757827599536143, 'f1-score': 0.7238859934671632, 'support': 1852.0}, 'weighted avg': {'precision': 0.891852340573561, 'recall': 0.8990280777537797, 'f1-score': 0.8820482011076873, 'support': 1852.0}}

## 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: 5e-06
- train_batch_size: 22
- eval_batch_size: 22
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 88
- total_eval_batch_size: 88
- 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: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Classification Report                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
|:-------------:|:-----:|:----:|:---------------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:|
| No log        | 1.0   | 71   | 0.2510          | {'0': {'precision': 0.8783185840707964, 'recall': 0.9974874371859297, 'f1-score': 0.9341176470588235, 'support': 1592.0}, '1': {'precision': 0.9090909090909091, 'recall': 0.15384615384615385, 'f1-score': 0.2631578947368421, 'support': 260.0}, 'accuracy': 0.8790496760259179, 'macro avg': {'precision': 0.8937047465808527, 'recall': 0.5756667955160417, 'f1-score': 0.5986377708978328, 'support': 1852.0}, 'weighted avg': {'precision': 0.8826386728965142, 'recall': 0.8790496760259179, 'f1-score': 0.839922433449906, 'support': 1852.0}} |
| No log        | 2.0   | 142  | 0.2290          | {'0': {'precision': 0.9048991354466859, 'recall': 0.9861809045226131, 'f1-score': 0.9437932070934776, 'support': 1592.0}, '1': {'precision': 0.811965811965812, 'recall': 0.36538461538461536, 'f1-score': 0.5039787798408488, 'support': 260.0}, 'accuracy': 0.8990280777537797, 'macro avg': {'precision': 0.858432473706249, 'recall': 0.6757827599536143, 'f1-score': 0.7238859934671632, 'support': 1852.0}, 'weighted avg': {'precision': 0.891852340573561, 'recall': 0.8990280777537797, 'f1-score': 0.8820482011076873, 'support': 1852.0}}   |


### Framework versions

- Transformers 4.53.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1