bert-base-uncased_news_ft – AI Model by GTsky | AlphaNeural AI

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GTsky/
bert-base-uncased_news_ft

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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_news_ft

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: 0.8121
Accuracy: 0.8433
F1: 0.8433
Precision: 0.8400

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: 0.0002
train_batch_size: 128
eval_batch_size: 128
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	Accuracy	F1	Precision
No log	1.0	322	0.6194	0.8121	0.8121	0.8278
0.5669	2.0	644	0.5412	0.8365	0.8361	0.8354
0.5669	3.0	966	0.5892	0.8403	0.8405	0.8412
0.1391	4.0	1288	0.7124	0.8392	0.8392	0.8333
0.1391	5.0	1610	0.8121	0.8433	0.8433	0.8400

Framework versions

Transformers 4.33.0
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3