---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-small
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: testhehehe
  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. -->

# testhehehe

This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on the data/originality_aidetector dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6675
- Accuracy: 0.667
- True Positive: 0.0
- False Negative: 1.0
- False Positive: 0.0
- True Negative: 1.0
- F1: 0.8002

## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | True Positive | False Negative | False Positive | True Negative | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:-------------:|:--------------:|:--------------:|:-------------:|:------:|
| No log        | 0.4375 | 7    | 0.7175          | 0.333    | 1.0           | 0.0            | 1.0            | 0.0           | 0.0    |
| No log        | 0.875  | 14   | 0.6894          | 0.679    | 0.0871        | 0.9129         | 0.0255         | 0.9745        | 0.802  |
| No log        | 1.3125 | 21   | 0.6765          | 0.667    | 0.0           | 1.0            | 0.0            | 1.0           | 0.8002 |
| No log        | 1.75   | 28   | 0.6675          | 0.667    | 0.0           | 1.0            | 0.0            | 1.0           | 0.8002 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0+cu121
- Datasets 2.19.2
- Tokenizers 0.20.0