human-vs-AI_bert-classifier – AI Model by tomerz14 | AlphaNeural AI

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tomerz14/
human-vs-AI_bert-classifier

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

text-embeddings-inference

endpoints_compatible

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human-vs-AI_bert-classifier

This model is a fine-tuned version of 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