bert_sst2_padding60model – AI Model by Realgon | AlphaNeural AI

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Realgon/
bert_sst2_padding60model

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text-classification

generated_from_trainer

google-bert/bert-base-uncased

autotrain_compatible

endpoints_compatible

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bert_sst2_padding60model

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: 0.7774
Accuracy: 0.9187

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
No log	1.0	433	0.2213	0.9149
0.3202	2.0	866	0.3212	0.9088
0.1548	3.0	1299	0.4507	0.9083
0.0661	4.0	1732	0.5928	0.9094
0.0312	5.0	2165	0.5448	0.9105
0.0203	6.0	2598	0.5419	0.9149
0.0219	7.0	3031	0.6287	0.9083
0.0219	8.0	3464	0.6658	0.9143
0.0069	9.0	3897	0.6251	0.9121
0.013	10.0	4330	0.6766	0.9127
0.01	11.0	4763	0.6689	0.9105
0.0055	12.0	5196	0.7376	0.9132
0.0057	13.0	5629	0.6735	0.9154
0.0084	14.0	6062	0.6908	0.9204
0.0084	15.0	6495	0.7107	0.9182
0.0036	16.0	6928	0.7741	0.9138
0.0017	17.0	7361	0.7156	0.9198
0.0041	18.0	7794	0.7829	0.9149
0.0005	19.0	8227	0.7700	0.9176
0.0004	20.0	8660	0.7774	0.9187

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3