N_bert_twitterfin_padding0model – AI Model by Realgon | AlphaNeural AI | AlphaNeural AI

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Realgon/
N_bert_twitterfin_padding0model

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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N_bert_twitterfin_padding0model

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: 0.9529
Accuracy: 0.8915

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5773	1.0	597	0.3668	0.8622
0.3227	2.0	1194	0.3236	0.8869
0.2252	3.0	1791	0.4392	0.8899
0.1332	4.0	2388	0.6509	0.8802
0.0963	5.0	2985	0.6162	0.8853
0.0415	6.0	3582	0.6892	0.8915
0.0368	7.0	4179	0.7563	0.8882
0.0285	8.0	4776	0.7581	0.8790
0.0283	9.0	5373	0.8500	0.8903
0.0233	10.0	5970	0.8538	0.8882
0.0147	11.0	6567	0.8992	0.8836
0.011	12.0	7164	0.8833	0.8907
0.0078	13.0	7761	0.8897	0.8865
0.0057	14.0	8358	0.8911	0.8907
0.0048	15.0	8955	0.9121	0.8899
0.0044	16.0	9552	0.9422	0.8874
0.0037	17.0	10149	0.9149	0.8924
0.0014	18.0	10746	0.9300	0.8920
0.0018	19.0	11343	0.9471	0.8924
0.0013	20.0	11940	0.9529	0.8915

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3