distilroberta-base-fake_news_detector-Am09 – AI Model by Am09 | AlphaNeural AI

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Am09/
distilroberta-base-fake_news_detector-Am09

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text-classification

generated_from_trainer

distilbert/distilroberta-base

autotrain_compatible

endpoints_compatible

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results

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

Loss: 0.0022
Acc: 0.9997
Precision: 0.9997
Recall: 0.9997
F1 score: 0.9997

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: 5e-05
train_batch_size: 32
eval_batch_size: 32
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: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Acc	Precision	Recall	F1 score
0.0069	0.0989	100	0.0401	0.9928	0.9927	0.9930	0.9928
0.0262	0.1978	200	0.0143	0.9975	0.9975	0.9975	0.9975
0.0118	0.2967	300	0.0098	0.9983	0.9983	0.9983	0.9983
0.0135	0.3956	400	0.0088	0.9989	0.9989	0.9989	0.9989
0.0163	0.4946	500	0.0136	0.9981	0.9980	0.9981	0.9980
0.0078	0.5935	600	0.0114	0.9986	0.9986	0.9986	0.9986
0.0103	0.6924	700	0.0132	0.9983	0.9983	0.9983	0.9983
0.0041	0.7913	800	0.0122	0.9986	0.9986	0.9986	0.9986
0.0098	0.8902	900	0.0078	0.9989	0.9989	0.9989	0.9989
0.0045	0.9891	1000	0.0047	0.9989	0.9989	0.9989	0.9989

Framework versions

Transformers 4.44.2
Pytorch 2.4.0
Datasets 3.0.0
Tokenizers 0.19.1