distilbert-uncased-finetuned-toxic-comments-detection – AI Model by tillschwoerer | AlphaNeural AI

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tillschwoerer/
distilbert-uncased-finetuned-toxic-comments-detection

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert-uncased-finetuned-toxic-comments-detection

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

Loss: 0.1520
Accuracy: 0.95
Precision: 0.7391
Recall: 0.8095
F1: 0.7727

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: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall	F1
0.3892	1.0	50	0.2808	0.895	0.0	0.0	0.0
0.219	2.0	100	0.1732	0.93	0.8182	0.4286	0.5625
0.1313	3.0	150	0.1515	0.95	0.7391	0.8095	0.7727
0.0924	4.0	200	0.1520	0.95	0.7391	0.8095	0.7727
0.0749	5.0	250	0.1540	0.96	0.8095	0.8095	0.8095

Framework versions

Transformers 4.30.1
Pytorch 2.0.1+cu118
Tokenizers 0.13.3