distilbert_sst5_padding0model – AI Model by Realgon | AlphaNeural AI

You can deploy this model and start earning money today!

Realgon/
distilbert_sst5_padding0model

like

0

text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

Views

No views yet

distilbert_sst5_padding0model

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: 4.1295
Accuracy: 0.5018

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
1.2692	1.0	534	1.2088	0.4462
1.0128	2.0	1068	1.1091	0.5299
0.8129	3.0	1602	1.1930	0.5262
0.6431	4.0	2136	1.3783	0.5213
0.4776	5.0	2670	1.7332	0.4783
0.3481	6.0	3204	1.7883	0.5140
0.2633	7.0	3738	2.1206	0.4955
0.191	8.0	4272	2.3658	0.5054
0.1627	9.0	4806	2.6203	0.5149
0.1387	10.0	5340	3.0193	0.4955
0.1049	11.0	5874	3.3081	0.5014
0.0888	12.0	6408	3.5941	0.4959
0.0689	13.0	6942	3.6559	0.5095
0.0615	14.0	7476	3.7450	0.5090
0.0426	15.0	8010	3.9371	0.5032
0.0372	16.0	8544	4.0202	0.5086
0.0255	17.0	9078	4.1399	0.4982
0.0221	18.0	9612	4.1091	0.5045
0.0237	19.0	10146	4.1077	0.5009
0.0206	20.0	10680	4.1295	0.5018

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu117
Datasets 2.14.5
Tokenizers 0.13.3