bert-base-uncased-textCLS-RHEOLOGY-20230912-2 – AI Model by jonas-luehrs | AlphaNeural AI

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jonas-luehrs/
bert-base-uncased-textCLS-RHEOLOGY-20230912-2

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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bert-base-uncased-textCLS-RHEOLOGY-20230912-2

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: 0.7536
F1: 0.7530
Precision: 0.7648
Recall: 0.7531
Accuracy: 0.7531

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: 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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Precision	Recall	Accuracy
1.2688	1.0	46	0.9905	0.6157	0.5887	0.6543	0.6543
0.8139	2.0	92	0.7606	0.6299	0.6038	0.6605	0.6605
0.5876	3.0	138	0.7458	0.7252	0.7330	0.7284	0.7284
0.4569	4.0	184	0.7387	0.7533	0.7683	0.7531	0.7531
0.3684	5.0	230	0.7536	0.7530	0.7648	0.7531	0.7531

Framework versions

Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3