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

# edu-modernbert

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: 0.2863
- Precision: 0.5402
- Recall: 0.3945
- F1: 0.4305
- Accuracy: 0.6822

## 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: 0.0003
- train_batch_size: 1024
- eval_batch_size: 512
- seed: 0
- 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: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 0       | 0    | 1.7219          | 0.1827    | 0.1714 | 0.0934 | 0.2345   |
| 0.3195        | 2.4331  | 1000 | 0.3180          | 0.5267    | 0.3632 | 0.3841 | 0.6562   |
| 0.3096        | 4.8662  | 2000 | 0.3028          | 0.5275    | 0.3827 | 0.4108 | 0.6652   |
| 0.3027        | 7.2993  | 3000 | 0.2985          | 0.5332    | 0.3905 | 0.4223 | 0.6681   |
| 0.3004        | 9.7324  | 4000 | 0.2919          | 0.5392    | 0.3867 | 0.4204 | 0.6774   |
| 0.2965        | 12.1655 | 5000 | 0.2896          | 0.5345    | 0.3970 | 0.4311 | 0.6788   |
| 0.2942        | 14.5985 | 6000 | 0.2885          | 0.5355    | 0.3960 | 0.4312 | 0.6819   |
| 0.287         | 17.0316 | 7000 | 0.2912          | 0.5360    | 0.3813 | 0.4170 | 0.6828   |
| 0.2893        | 19.4647 | 8000 | 0.2863          | 0.5402    | 0.3945 | 0.4305 | 0.6822   |


### Framework versions

- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0