olid_baseline_v2 – AI Model by iTroned | AlphaNeural AI

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iTroned/
olid_baseline_v2

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google-bert/bert-base-uncased

endpoints_compatible

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olid_baseline_v2

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: 0.6879
Accuracy Offensive: 0.7987
F1 Macro Offensive: 0.7698
F1 Weighted Offensive: 0.7950

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-06
train_batch_size: 4
eval_batch_size: 4
seed: 42
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: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy Offensive	F1 Macro Offensive	F1 Weighted Offensive
0.5313	1.0	2648	0.6233	0.7934	0.7465	0.7802
0.5213	2.0	5296	0.6879	0.7987	0.7698	0.7950
0.5066	3.0	7944	0.8322	0.7900	0.7641	0.7883
0.3509	4.0	10592	1.0364	0.7893	0.7679	0.7896
0.2981	5.0	13240	1.2036	0.7893	0.7663	0.7889
0.1856	6.0	15888	1.5147	0.7753	0.7586	0.7782

Framework versions

Transformers 4.50.2
Pytorch 2.6.0+cu124
Datasets 3.0.1
Tokenizers 0.21.1