ia-detection-roberta-base – AI Model by arincon | AlphaNeural AI

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arincon/
ia-detection-roberta-base

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text-classification

generated_from_trainer

autextification2023

autotrain_compatible

endpoints_compatible

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ia-detection-roberta-base

This model is a fine-tuned version of roberta-base on the autextification2023 dataset. It achieves the following results on the evaluation set:

Loss: 0.6928
Accuracy: 0.5126
F1: 0.6777
Precision: 0.5126
Recall: 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: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.7021	1.0	3808	0.6950	0.5052	0.0	0.0	0.0
0.6936	2.0	7616	0.6937	0.4948	0.6621	0.4948	1.0
0.692	3.0	11424	0.6936	0.5052	0.0	0.0	0.0
0.6988	4.0	15232	0.6952	0.4948	0.6621	0.4948	1.0
0.6951	5.0	19040	0.6931	0.5052	0.0	0.0	0.0

Framework versions

Transformers 4.26.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.13.3