guilbert-base-uncased-guilt-detection – AI Model by mekjr1 | AlphaNeural AI

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mekjr1/
guilbert-base-uncased-guilt-detection

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text-classification

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autotrain_compatible

endpoints_compatible

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guilbert-base-uncased-guilt-detection

This model is a fine-tuned version of mekjr1/guilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6689
Accuracy: 0.7864
F1: 0.7863
Precision: 0.7865
Recall: 0.7864

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: 64
eval_batch_size: 64
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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall
0.447	1.0	2042	0.4435	0.7957	0.7957	0.7958	0.7957
0.3744	2.0	4084	0.4519	0.8002	0.8001	0.8006	0.8002
0.2506	3.0	6126	0.5618	0.7966	0.7964	0.7980	0.7966
0.1525	4.0	8168	0.6689	0.7864	0.7863	0.7865	0.7864

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2