---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
model-index:
- name: modernbert-acceptance-classifier-final
  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. -->

# modernbert-acceptance-classifier-final

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: 0.6494
- F1: 0.8156
- Precision: 0.8160
- Recall: 0.8157

## 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: 1.2448932804037876e-05
- train_batch_size: 10
- 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
- lr_scheduler_warmup_ratio: 0.17030843157226483
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| 0.4105        | 1.0   | 1609 | 0.3929          | 0.8180 | 0.8180    | 0.8180 |
| 0.375         | 2.0   | 3218 | 0.4030          | 0.8222 | 0.8262    | 0.8229 |
| 0.185         | 3.0   | 4827 | 0.6494          | 0.8156 | 0.8160    | 0.8157 |


### Framework versions

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