toxicBERT-params – AI Model by troesy | AlphaNeural AI

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toxicBERT-params

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token-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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toxicBERT-params

This model is a fine-tuned version of unitary/toxic-bert on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.2938
Precision: 0.0
Recall: 0.0
F1: 0.0
Accuracy: 0.9174

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	174	0.2364	0.0	0.0	0.0	0.9077
No log	2.0	348	0.2113	0.0	0.0	0.0	0.9190
0.2654	3.0	522	0.2195	0.0	0.0	0.0	0.9223
0.2654	4.0	696	0.2401	0.0	0.0	0.0	0.9211
0.2654	5.0	870	0.2679	0.0	0.0	0.0	0.9198
0.0844	6.0	1044	0.2930	0.0	0.0	0.0	0.9138
0.0844	7.0	1218	0.2938	0.0	0.0	0.0	0.9174

Framework versions

Transformers 4.24.0
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.2