soft-search – AI Model by evamaxfield | AlphaNeural AI

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evamaxfield/
soft-search

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased-finetuned-sst-2-english

autotrain_compatible

endpoints_compatible

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soft-search

This model is a fine-tuned version of distilbert-base-uncased-finetuned-sst-2-english on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5558
F1: 0.5960
Accuracy: 0.7109
Precision: 0.5769
Recall: 0.6164

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: 3e-05
train_batch_size: 12
eval_batch_size: 12
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	F1	Accuracy	Precision	Recall
0.5939	1.0	71	0.5989	0.0533	0.6635	1.0	0.0274
0.5903	2.0	142	0.5558	0.5960	0.7109	0.5769	0.6164
0.4613	3.0	213	0.6670	0.5641	0.6777	0.5301	0.6027
0.4454	4.0	284	0.7647	0.5541	0.6872	0.5467	0.5616
0.2931	5.0	355	0.8726	0.5139	0.6682	0.5211	0.5068

Framework versions

Transformers 4.25.1
Pytorch 1.13.1+cu117
Datasets 2.8.0
Tokenizers 0.13.2