xlm-roberta-base-chn-finetuned-augmentation-LUNAR – AI Model by sercetexam9 | AlphaNeural AI

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sercetexam9/
xlm-roberta-base-chn-finetuned-augmentation-LUNAR

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text-classification

generated_from_trainer

FacebookAI/xlm-roberta-base

autotrain_compatible

endpoints_compatible

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xlm-roberta-base-chn-finetuned-augmentation-LUNAR

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

Loss: 0.2528
F1: 0.7723
Roc Auc: 0.8558
Accuracy: 0.6929

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: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.2672	1.0	315	0.2663	0.3994	0.6673	0.5099
0.2127	2.0	630	0.2110	0.5656	0.7471	0.5998
0.1861	3.0	945	0.2008	0.5724	0.7511	0.6158
0.1409	4.0	1260	0.1933	0.6684	0.7884	0.6460
0.0937	5.0	1575	0.1901	0.7184	0.8288	0.6738
0.0778	6.0	1890	0.1895	0.7253	0.8187	0.6866
0.0552	7.0	2205	0.2191	0.7197	0.8435	0.6587
0.0435	8.0	2520	0.2388	0.7405	0.8634	0.6643
0.0395	9.0	2835	0.2352	0.7569	0.8469	0.6770
0.0273	10.0	3150	0.2401	0.7563	0.8553	0.6993
0.0317	11.0	3465	0.2485	0.7465	0.8527	0.6866
0.0134	12.0	3780	0.2528	0.7723	0.8558	0.6929
0.0106	13.0	4095	0.2822	0.7220	0.8386	0.6603
0.0107	14.0	4410	0.2685	0.7536	0.8451	0.6881
0.01	15.0	4725	0.2655	0.7583	0.8467	0.6993
0.0056	16.0	5040	0.2748	0.7618	0.8531	0.6993

Framework versions

Transformers 4.45.1
Pytorch 2.4.0
Datasets 3.0.1
Tokenizers 0.20.0