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

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mekjr1/
bert-base-uncased-guilt-detection

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-base-uncased-guilt-detection

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

Loss: 0.6646
Accuracy: 0.7831
F1: 0.7830
Precision: 0.7836
Recall: 0.7831

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
0.45	1.0	2042	0.4409	0.7979	0.7979	0.7979	0.7979
0.3824	2.0	4084	0.4561	0.7990	0.7989	0.7993	0.7990
0.2573	3.0	6126	0.5581	0.7900	0.7895	0.7930	0.7900
0.1548	4.0	8168	0.6646	0.7831	0.7830	0.7836	0.7831

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cu116
Datasets 2.10.1
Tokenizers 0.13.2