---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: featured-articles
  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. -->

# featured-articles

This model is a fine-tuned version of [answerdotai/ModernBERT-base](https://huggingface.co/answerdotai/ModernBERT-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9620
- Weighted F1: 0.6740
- Accepted Precision: 0.7453
- Accepted Recall: 0.7790
- Accepted F1: 0.7618
- Rejected Precision: 0.5273
- Rejected Recall: 0.4807
- Rejected F1: 0.5029
- Accuracy: 0.6779

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Weighted F1 | Accepted Precision | Accepted Recall | Accepted F1 | Rejected Precision | Rejected Recall | Rejected F1 | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:-----------:|:------------------:|:---------------:|:-----------:|:------------------:|:---------------:|:-----------:|:--------:|
| 0.6595        | 1.0   | 267  | 0.6187          | 0.6876      | 0.752              | 0.7989          | 0.7747      | 0.5535             | 0.4862          | 0.5176      | 0.6929   |
| 0.4807        | 2.0   | 534  | 0.7625          | 0.5677      | 0.8030             | 0.4504          | 0.5771      | 0.4226             | 0.7845          | 0.5493      | 0.5637   |
| 0.3013        | 3.0   | 801  | 1.7444          | 0.6577      | 0.7105             | 0.9178          | 0.8010      | 0.6282             | 0.2707          | 0.3784      | 0.6985   |
| 0.0381        | 4.0   | 1068 | 1.9620          | 0.6740      | 0.7453             | 0.7790          | 0.7618      | 0.5273             | 0.4807          | 0.5029      | 0.6779   |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.2.2
- Datasets 3.1.0
- Tokenizers 0.21.0