---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: modernbert-tr-classifier
  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. -->

# modernbert-tr-classifier

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2880
- F1: 0.8888
- Accuracy: 0.8898

## 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: 8e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.98) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:--------:|
| 1.3439        | 1.0   | 146  | 0.7811          | 0.7564 | 0.7510   |
| 0.5346        | 2.0   | 292  | 0.5727          | 0.8162 | 0.8163   |
| 0.2959        | 3.0   | 438  | 0.5732          | 0.8061 | 0.8082   |
| 0.1828        | 4.0   | 584  | 0.5832          | 0.8494 | 0.8490   |
| 0.1113        | 5.0   | 730  | 0.8149          | 0.8564 | 0.8571   |
| 0.0811        | 6.0   | 876  | 0.9747          | 0.8366 | 0.8367   |
| 0.0427        | 7.0   | 1022 | 1.0021          | 0.8812 | 0.8816   |
| 0.0493        | 8.0   | 1168 | 1.0971          | 0.8614 | 0.8612   |
| 0.0494        | 9.0   | 1314 | 1.3082          | 0.8454 | 0.8449   |
| 0.0205        | 10.0  | 1460 | 1.2811          | 0.8588 | 0.8571   |
| 0.0079        | 11.0  | 1606 | 1.2820          | 0.8534 | 0.8531   |
| 0.0214        | 12.0  | 1752 | 1.0864          | 0.8622 | 0.8612   |
| 0.0113        | 13.0  | 1898 | 1.0554          | 0.8853 | 0.8857   |
| 0.005         | 14.0  | 2044 | 1.3213          | 0.8784 | 0.8776   |
| 0.0023        | 15.0  | 2190 | 1.2395          | 0.8734 | 0.8735   |
| 0.0007        | 16.0  | 2336 | 1.3468          | 0.8870 | 0.8857   |
| 0.0006        | 17.0  | 2482 | 1.3490          | 0.8813 | 0.8816   |
| 0.0007        | 18.0  | 2628 | 1.2886          | 0.8888 | 0.8898   |
| 0.0004        | 19.0  | 2774 | 1.2850          | 0.8888 | 0.8898   |
| 0.0003        | 20.0  | 2920 | 1.2880          | 0.8888 | 0.8898   |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.21.0