sentence_bert-base-uncased-finetuned-SENTENCE – AI Model by ali2066 | AlphaNeural AI

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sentence_bert-base-uncased-finetuned-SENTENCE

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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sentence_bert-base-uncased-finetuned-SENTENCE

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: 0.4834
Precision: 0.8079
Recall: 1.0
F1: 0.8938
Accuracy: 0.8079

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: 0.0001
train_batch_size: 32
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	13	0.3520	0.8889	1.0	0.9412	0.8889
No log	2.0	26	0.3761	0.8889	1.0	0.9412	0.8889
No log	3.0	39	0.3683	0.8889	1.0	0.9412	0.8889
No log	4.0	52	0.3767	0.8889	1.0	0.9412	0.8889
No log	5.0	65	0.3834	0.8889	1.0	0.9412	0.8889

Framework versions

Transformers 4.15.0
Pytorch 1.10.1+cu113
Datasets 1.18.0
Tokenizers 0.10.3