testing1 – AI Model by SpicyCorpse | AlphaNeural AI

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SpicyCorpse/
testing1

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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testing1

This model is a fine-tuned version of bert-base-uncased on the massive dataset. It achieves the following results on the evaluation set:

Loss: 0.7285
Accuracy: 0.8928

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: 16
eval_batch_size: 16
seed: 33
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.4751	1.0	720	0.6154	0.8593
0.4363	2.0	1440	0.4945	0.8800
0.2325	3.0	2160	0.5608	0.8834
0.1349	4.0	2880	0.6023	0.8800
0.0887	5.0	3600	0.6301	0.8869
0.0575	6.0	4320	0.6649	0.8898
0.0358	7.0	5040	0.7023	0.8908
0.0218	8.0	5760	0.7419	0.8913
0.0184	9.0	6480	0.7285	0.8928
0.0126	10.0	7200	0.7207	0.8908
0.0072	11.0	7920	0.7453	0.8923
0.0056	12.0	8640	0.7746	0.8918

Framework versions

Transformers 4.36.2
Pytorch 2.0.1+cu117
Datasets 2.15.0
Tokenizers 0.15.0