---
library_name: transformers
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: human-vs-AI_bert-classifier
  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. -->

# human-vs-AI_bert-classifier

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0011
- Accuracy: 1.0
- F1: 1.0
- Roc Auc: 1.0

## 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: 32
- seed: 14
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1  | Roc Auc |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---:|:-------:|
| 0.333         | 0.2475 | 50   | 0.0377          | 1.0      | 1.0 | 1.0     |
| 0.0108        | 0.4950 | 100  | 0.0023          | 1.0      | 1.0 | 1.0     |
| 0.0105        | 0.7426 | 150  | 0.0015          | 1.0      | 1.0 | 1.0     |
| 0.0104        | 0.9901 | 200  | 0.0011          | 1.0      | 1.0 | 1.0     |


### Framework versions

- Transformers 4.48.0
- Pytorch 2.6.0
- Datasets 3.6.0
- Tokenizers 0.21.4