---
library_name: transformers
base_model: answerdotai/ModernBERT-large
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: ModernEMO-wheel-large-multilabel
  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. -->

# ModernEMO-wheel-large-multilabel

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: 0.1904
- F1: 0.6756
- Roc Auc: 0.8001
- Accuracy: 0.5859

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
| 0.2058        | 1.0   | 5427  | 0.1861          | 0.6627 | 0.7864  | 0.5676   |
| 0.1458        | 2.0   | 10854 | 0.1904          | 0.6756 | 0.8001  | 0.5859   |


### Framework versions

- Transformers 4.49.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0