---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: valueeval24-modern-bert
  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. -->

# valueeval24-modern-bert

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: 0.1613
- F1: 0.3178
- Roc Auc: 0.6190
- Accuracy: 0.1954

## 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: 8
- eval_batch_size: 8
- seed: 2024
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.1463        | 1.0   | 2883  | 0.1052          | 0.1633 | 0.5464  | 0.0854   |
| 0.1003        | 2.0   | 5766  | 0.0995          | 0.2146 | 0.5640  | 0.1188   |
| 0.0907        | 3.0   | 8649  | 0.0981          | 0.2777 | 0.5899  | 0.1662   |
| 0.0806        | 4.0   | 11532 | 0.1001          | 0.3038 | 0.6035  | 0.1804   |
| 0.0685        | 5.0   | 14415 | 0.1048          | 0.3099 | 0.6094  | 0.1914   |
| 0.0549        | 6.0   | 17298 | 0.1104          | 0.3209 | 0.6177  | 0.1968   |
| 0.0412        | 7.0   | 20181 | 0.1158          | 0.3197 | 0.6198  | 0.1934   |
| 0.0285        | 8.0   | 23064 | 0.1232          | 0.3226 | 0.6210  | 0.1974   |
| 0.0184        | 9.0   | 25947 | 0.1312          | 0.3157 | 0.6186  | 0.1943   |
| 0.0114        | 10.0  | 28830 | 0.1381          | 0.3176 | 0.6192  | 0.1951   |
| 0.0071        | 11.0  | 31713 | 0.1463          | 0.3216 | 0.6216  | 0.1972   |
| 0.0047        | 12.0  | 34596 | 0.1542          | 0.3153 | 0.6168  | 0.1959   |
| 0.0032        | 13.0  | 37479 | 0.1613          | 0.3178 | 0.6190  | 0.1954   |


### Framework versions

- Transformers 4.53.0
- Pytorch 2.5.1+cu121
- Datasets 3.6.0
- Tokenizers 0.21.2