RuleBert-v0.1-k0 – AI Model by ribesstefano | AlphaNeural AI

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ribesstefano/
RuleBert-v0.1-k0

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text-classification

generated_from_trainer

classla/xlm-roberta-base-multilingual-text-genre-classifier

autotrain_compatible

endpoints_compatible

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ribesstefano/RuleBert-v0.1-k0

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

Loss: 0.3765
F1: 0.5087
Roc Auc: 0.6757
Accuracy: 0.0333

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: 4
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 4000
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	F1	Roc Auc	Accuracy
0.3621	0.14	250	0.3791	0.4861	0.6678	0.0458
0.3199	0.28	500	0.3754	0.4969	0.6730	0.0375
0.3135	0.41	750	0.3785	0.4965	0.6715	0.0458
0.3176	0.55	1000	0.3755	0.4988	0.6725	0.0333
0.3056	0.69	1250	0.3734	0.5100	0.6756	0.0667
0.3016	0.83	1500	0.3749	0.5076	0.6755	0.0333
0.3044	0.97	1750	0.3763	0.5014	0.6738	0.0125
0.3009	1.11	2000	0.3781	0.5073	0.6751	0.0333
0.3044	1.24	2250	0.3782	0.5089	0.6755	0.0417
0.2979	1.38	2500	0.3770	0.5047	0.6745	0.0167
0.2977	1.52	2750	0.3772	0.5114	0.6764	0.0417
0.2998	1.66	3000	0.3747	0.5107	0.6762	0.0375
0.2916	1.8	3250	0.3741	0.5096	0.6758	0.0375
0.3107	1.94	3500	0.3757	0.5056	0.6748	0.0208
0.3023	2.07	3750	0.3767	0.5069	0.6752	0.025
0.3069	2.21	4000	0.3765	0.5087	0.6757	0.0333

Framework versions

Transformers 4.36.2
Pytorch 2.1.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0