bert-base-uncased-finetuned-vr-comfort-description-review-epoch15-20221107_2125 – AI Model by jasonsheih | AlphaNeural AI

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jasonsheih/
bert-base-uncased-finetuned-vr-comfort-description-review-epoch15-20221107_2125

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-base-uncased-finetuned-vr-comfort-description-review-epoch15-20221107_2125

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: 1.0521
Accuracy: 0.8443
F1: 0.8449

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: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1
0.7304	1.0	157	0.5838	0.7521	0.6457
0.6062	2.0	314	0.5416	0.7593	0.7487
0.4363	3.0	471	0.4852	0.8120	0.8139
0.2679	4.0	628	0.5454	0.8204	0.8102
0.164	5.0	785	0.6908	0.8060	0.8162
0.112	6.0	942	0.7277	0.8287	0.8304
0.0759	7.0	1099	0.9089	0.8096	0.8192
0.0323	8.0	1256	0.8422	0.8551	0.8524
0.0174	9.0	1413	1.0020	0.8299	0.8357
0.0138	10.0	1570	0.9637	0.8491	0.8473
0.0057	11.0	1727	1.0195	0.8503	0.8411
0.0044	12.0	1884	1.0172	0.8455	0.8462
0.0035	13.0	2041	1.0056	0.8503	0.8487
0.002	14.0	2198	1.0554	0.8443	0.8451
0.0014	15.0	2355	1.0521	0.8443	0.8449

Framework versions

Transformers 4.13.0
Pytorch 1.11.0
Datasets 1.16.1
Tokenizers 0.10.3