distilbert_sst5_padding70model – AI Model by Realgon | AlphaNeural AI

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Realgon/
distilbert_sst5_padding70model

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert_sst5_padding70model

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: 3.9464
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
1.342	1.0	534	1.3172	0.3914
1.0595	2.0	1068	1.1123	0.5140
0.8701	3.0	1602	1.1455	0.5281
0.71	4.0	2136	1.3218	0.5163
0.5487	5.0	2670	1.5399	0.5027
0.4201	6.0	3204	1.7212	0.5005
0.3293	7.0	3738	1.8778	0.5113
0.2412	8.0	4272	2.0483	0.5158
0.207	9.0	4806	2.2857	0.5113
0.1778	10.0	5340	2.5679	0.5113
0.1325	11.0	5874	2.8006	0.5077
0.1154	12.0	6408	3.1458	0.4991
0.0927	13.0	6942	3.2323	0.5109
0.0801	14.0	7476	3.5445	0.4937
0.0542	15.0	8010	3.6395	0.5100
0.0515	16.0	8544	3.7555	0.5050
0.0369	17.0	9078	3.8901	0.5059
0.0381	18.0	9612	3.9145	0.5059
0.0265	19.0	10146	3.9511	0.5081
0.0244	20.0	10680	3.9464	0.5054

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3