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---
library_name: transformers
license: apache-2.0
base_model: answerdotai/ModernBERT-base
tags:
- generated_from_trainer
model-index:
- name: answerdotai-ModernBERT-base-ai-detector
  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. -->

# answerdotai-ModernBERT-base-ai-detector

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: 0.0036

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0505        | 0.2228 | 500  | 0.0214          |
| 0.0114        | 0.4456 | 1000 | 0.0110          |
| 0.0088        | 0.6684 | 1500 | 0.0032          |
| 0.0           | 0.8913 | 2000 | 0.0048          |
| 0.0068        | 1.1141 | 2500 | 0.0035          |
| 0.0           | 1.3369 | 3000 | 0.0040          |
| 0.0           | 1.5597 | 3500 | 0.0097          |
| 0.0053        | 1.7825 | 4000 | 0.0101          |
| 0.0           | 2.0053 | 4500 | 0.0053          |
| 0.0           | 2.2282 | 5000 | 0.0039          |
| 0.0017        | 2.4510 | 5500 | 0.0046          |
| 0.0           | 2.6738 | 6000 | 0.0043          |
| 0.0           | 2.8966 | 6500 | 0.0036          |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0