---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- roc_auc
model-index:
- name: ModernEMO-base
  results: []
datasets:
- Jsevisal/go_emotions_ekman
- google-research-datasets/go_emotions
pipeline_tag: text-classification
---

<!-- 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-base

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on [Jsevisal/go_emotions_ekman](https://huggingface.co/datasets/Jsevisal/go_emotions_ekman)
It achieves the following results on the evaluation set:
- Loss: 0.2224
- F1: 0.7037
- Roc Auc: 0.8143
- Accuracy: 0.6226

## 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: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.2162        | 1.0   | 2714 | 0.2049          | 0.6920 | 0.7979  | 0.6010   |
| 0.1553        | 2.0   | 5428 | 0.2224          | 0.7037 | 0.8143  | 0.6226   |


### Framework versions

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