distilbert-base-uncased-PINA-dfnew-2 – AI Model by GhifSmile | AlphaNeural AI

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GhifSmile/
distilbert-base-uncased-PINA-dfnew-2

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-PINA-dfnew-2

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

Loss: 0.3815
Accuracy: 0.9106
Precision: 0.7799
Recall: 0.7804

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision	Recall
1.5008	1.0	1002	0.6541	0.8482	0.6999	0.6173
0.4599	2.0	2004	0.4240	0.9004	0.7739	0.7641
0.2458	3.0	3006	0.3815	0.9106	0.7799	0.7804
0.1549	4.0	4008	0.3817	0.9206	0.8114	0.8064
0.0977	5.0	5010	0.4187	0.9194	0.8118	0.8031
0.0662	6.0	6012	0.4207	0.9213	0.8109	0.8085
0.0454	7.0	7014	0.4361	0.9226	0.8276	0.8199
0.0314	8.0	8016	0.4562	0.9233	0.8288	0.8209
0.023	9.0	9018	0.4657	0.9221	0.8272	0.8192
0.0185	10.0	10020	0.4620	0.9226	0.8278	0.8191

Framework versions

Transformers 4.28.0
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3