xlnet-large-cased-airlines-news-multi-label – AI Model by dahe827 | AlphaNeural AI

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dahe827/
xlnet-large-cased-airlines-news-multi-label

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text-classification

generated_from_trainer

xlnet/xlnet-large-cased

autotrain_compatible

endpoints_compatible

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xlnet-large-cased-airlines-news-multi-label

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

Loss: 0.2329
F1: 0.9001
Roc Auc: 0.6501
Hamming: 0.9145

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: 9e-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
lr_scheduler_warmup_steps: 150
num_epochs: 12

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Hamming
No log	1.0	128	0.2866	0.8594	0.5	0.9041
No log	2.0	256	0.2520	0.8955	0.5943	0.9130
No log	3.0	384	0.2431	0.8984	0.6493	0.9130
0.3656	4.0	512	0.2384	0.8984	0.6622	0.9115
0.3656	5.0	640	0.2329	0.9001	0.6501	0.9145
0.3656	6.0	768	0.2353	0.9000	0.6699	0.9130
0.3656	7.0	896	0.2336	0.8959	0.6735	0.9071
0.2788	8.0	1024	0.2318	0.8957	0.6606	0.9086
0.2788	9.0	1152	0.2327	0.8961	0.6606	0.9086
0.2788	10.0	1280	0.2317	0.8975	0.6545	0.9100
0.2788	11.0	1408	0.2311	0.8975	0.6545	0.9100
0.2659	12.0	1536	0.2309	0.8982	0.6554	0.9115

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.2
Tokenizers 0.19.1