Covid_Vaccine_Sentiment_Analysis_Bert_based_Model – AI Model by NewtonKimathi | AlphaNeural AI

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NewtonKimathi/
Covid_Vaccine_Sentiment_Analysis_Bert_based_Model

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text-classification

generated_from_trainer

google-bert/bert-base-cased

autotrain_compatible

endpoints_compatible

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Covid_Vaccine_Sentiment_Analysis_Bert_based_Model

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

Loss: 2.1070

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss
0.7469	0.5	500	0.7283
0.691	1.0	1000	0.6457
0.5828	1.5	1500	0.6741
0.5723	2.0	2000	0.6179
0.4145	2.5	2500	0.8410
0.4044	3.0	3000	0.7809
0.2592	3.5	3500	1.1192
0.2932	4.0	4000	1.2706
0.162	4.5	4500	1.3559
0.1846	5.0	5000	1.2930
0.0975	5.5	5500	1.4937
0.1228	6.0	6000	1.5674
0.0718	6.5	6500	1.6709
0.068	7.0	7000	1.8645
0.0478	7.5	7500	2.0231
0.0504	8.0	8000	1.8383
0.0245	8.5	8500	2.0527
0.0366	9.0	9000	2.0015
0.0197	9.5	9500	2.1190
0.0147	10.0	10000	2.1070

Framework versions

Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3