bert_twitterfin_padding10model – AI Model by Realgon | AlphaNeural AI

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Realgon/
bert_twitterfin_padding10model

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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bert_twitterfin_padding10model

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: 0.9864
Accuracy: 0.8886

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
0.6083	1.0	597	0.3625	0.8735
0.3327	2.0	1194	0.3208	0.8874
0.2233	3.0	1791	0.4562	0.8840
0.1362	4.0	2388	0.5298	0.8878
0.1043	5.0	2985	0.6050	0.8874
0.0391	6.0	3582	0.7192	0.8836
0.0386	7.0	4179	0.7127	0.8915
0.021	8.0	4776	0.7646	0.8752
0.0364	9.0	5373	0.7710	0.8890
0.0179	10.0	5970	0.7893	0.8899
0.0103	11.0	6567	0.8504	0.8920
0.009	12.0	7164	0.8612	0.8932
0.009	13.0	7761	0.9168	0.8874
0.0056	14.0	8358	0.9087	0.8865
0.0048	15.0	8955	0.9578	0.8840
0.0029	16.0	9552	0.9869	0.8869
0.0053	17.0	10149	0.9375	0.8890
0.0019	18.0	10746	0.9803	0.8886
0.0022	19.0	11343	0.9975	0.8903
0.0009	20.0	11940	0.9864	0.8886

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3