distilbert_sst5_padding80model – AI Model by Realgon | AlphaNeural AI

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Realgon/
distilbert_sst5_padding80model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert_sst5_padding80model

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

Loss: 3.9171
Accuracy: 0.5054

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
1.3494	1.0	534	1.2564	0.4181
1.0617	2.0	1068	1.1176	0.4982
0.8787	3.0	1602	1.1842	0.5149
0.7134	4.0	2136	1.2718	0.5163
0.5548	5.0	2670	1.4860	0.5104
0.4256	6.0	3204	1.7135	0.4986
0.3318	7.0	3738	1.8871	0.4928
0.2476	8.0	4272	2.0403	0.5127
0.1946	9.0	4806	2.2836	0.4982
0.1737	10.0	5340	2.5511	0.5027
0.1482	11.0	5874	2.8407	0.5036
0.1166	12.0	6408	3.1513	0.4959
0.0901	13.0	6942	3.2833	0.5027
0.0825	14.0	7476	3.4168	0.5041
0.0551	15.0	8010	3.5105	0.5032
0.0492	16.0	8544	3.6475	0.5014
0.0367	17.0	9078	3.7859	0.5045
0.0351	18.0	9612	3.8480	0.4977
0.0316	19.0	10146	3.9006	0.5023
0.0264	20.0	10680	3.9171	0.5054

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3