cate-ts – AI Model by tangminhanh | AlphaNeural AI

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tangminhanh/
cate-ts

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text-classification

generated_from_trainer

tangminhanh/techgroup-ts

autotrain_compatible

endpoints_compatible

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results

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

Loss: 0.0214
Accuracy: 0.8673
F1: 0.8828
Precision: 0.8907
Recall: 0.8750

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	F1	Precision	Recall
0.0959	1.0	816	0.0287	0.7330	0.7966	0.8666	0.7371
0.0223	2.0	1632	0.0203	0.8256	0.8587	0.8922	0.8277
0.0171	3.0	2448	0.0197	0.8348	0.8639	0.8824	0.8463
0.0116	4.0	3264	0.0194	0.8486	0.8708	0.8873	0.8548
0.0101	5.0	4080	0.0198	0.8532	0.8704	0.8798	0.8612
0.008	6.0	4896	0.0200	0.8550	0.8742	0.8872	0.8615
0.0065	7.0	5712	0.0204	0.8614	0.8775	0.8867	0.8686
0.0056	8.0	6528	0.0208	0.8587	0.8768	0.8858	0.8679
0.0048	9.0	7344	0.0214	0.8624	0.8781	0.8875	0.8689
0.0044	10.0	8160	0.0214	0.8673	0.8828	0.8907	0.8750

Framework versions

Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1