distilbert-base-uncased-distilled-clinc – AI Model by AndreasHansenAU | AlphaNeural AI

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AndreasHansenAU/
distilbert-base-uncased-distilled-clinc

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text-classification

generated_from_trainer

distilbert/distilbert-base-uncased

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-distilled-clinc

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: 0.1199
Accuracy: 0.9510

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: 0.0002537026657483439
train_batch_size: 48
eval_batch_size: 48
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 15

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.5456	1.0	318	0.1923	0.9048
0.1494	2.0	636	0.1698	0.9216
0.114	3.0	954	0.1448	0.9410
0.0934	4.0	1272	0.1410	0.9397
0.0839	5.0	1590	0.1309	0.9490
0.0804	6.0	1908	0.1332	0.9442
0.0801	7.0	2226	0.1321	0.9452
0.0762	8.0	2544	0.1330	0.9468
0.0741	9.0	2862	0.1293	0.9484
0.0732	10.0	3180	0.1264	0.9468
0.0717	11.0	3498	0.1244	0.9452
0.0702	12.0	3816	0.1214	0.9484
0.0694	13.0	4134	0.1209	0.9477
0.0686	14.0	4452	0.1203	0.9506
0.0678	15.0	4770	0.1199	0.9510

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1