test_train_offensive – AI Model by iTroned | AlphaNeural AI

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iTroned/
test_train_offensive

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distilbert/distilbert-base-uncased

endpoints_compatible

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test_train_offensive

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: 0.5260
Accuracy Offensive: 0.7976
F1 Offensive: 0.7944
Accuracy Targeted: 0.7704
F1 Targeted: 0.7526
Accuracy Stance: 0.7530
F1 Stance: 0.7266

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
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy Offensive	F1 Offensive	Accuracy Targeted	F1 Targeted	Accuracy Stance	F1 Stance
No log	1.0	373	0.5385	0.8074	0.7981	0.7742	0.7476	0.7432	0.6882
0.5669	2.0	746	0.5260	0.7976	0.7944	0.7704	0.7526	0.7530	0.7266
0.459	3.0	1119	0.5472	0.7870	0.7888	0.7598	0.7479	0.7485	0.7348
0.459	4.0	1492	0.5918	0.7908	0.7861	0.7628	0.7470	0.7485	0.7247

Framework versions

Transformers 4.45.2
Pytorch 2.5.0+cu124
Datasets 3.0.1
Tokenizers 0.20.1