ts_cate – AI Model by kmcs-casulit | AlphaNeural AI

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kmcs-casulit/
ts_cate

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tangminhanh/ts_tg

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ts_cate

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

Loss: 0.0263
Accuracy: 0.8555
F1: 0.8736
Precision: 0.8824
Recall: 0.8649

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: 32
eval_batch_size: 64
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
No log	1.0	404	0.0458	0.6802	0.7650	0.8750	0.6796
0.1001	2.0	808	0.0318	0.7717	0.8259	0.8817	0.7767
0.0321	3.0	1212	0.0278	0.8251	0.8564	0.8862	0.8286
0.0215	4.0	1616	0.0256	0.8322	0.8627	0.8909	0.8363
0.0161	5.0	2020	0.0256	0.8455	0.8679	0.8812	0.8551
0.0161	6.0	2424	0.0259	0.8499	0.8711	0.8831	0.8594
0.0124	7.0	2828	0.0255	0.8536	0.8713	0.8836	0.8594
0.0105	8.0	3232	0.0262	0.8533	0.8723	0.8836	0.8612
0.0087	9.0	3636	0.0261	0.8567	0.8746	0.8838	0.8656
0.0078	10.0	4040	0.0263	0.8555	0.8736	0.8824	0.8649

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1