---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: valueeval24-bert-phase1-initialfreeze
  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-bert-phase1-initialfreeze

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: 0.1085
- F1: 0.1171
- Roc Auc: 0.5320
- Accuracy: 0.0580

## 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: 0.00025
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.1192        | 1.0   | 2883 | 0.1084          | 0.0885 | 0.5234  | 0.0445   |
| 0.0927        | 2.0   | 5766 | 0.1085          | 0.1171 | 0.5320  | 0.0580   |


### Framework versions

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