distilbert-base-multilingual-cased-misogyny-sexism-decay0.01-fr-outofdomain

This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 3.1385
• Accuracy: 0.2369
• F1: 0.1919
• Precision: 0.1087
• Recall: 0.8148
• Mae: 0.7631
• Tn: 1279
• Fp: 6491
• Fn: 180
• Tp: 792

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	Mae	Tn	Fp	Fn	Tp
0.2166	1.0	2233	1.2875	0.3377	0.2025	0.1169	0.7562	0.6623	2217	5553	237	735
0.2068	2.0	4466	1.8399	0.3141	0.2154	0.1234	0.8467	0.6859	1923	5847	149	823
0.2015	3.0	6699	1.5430	0.3543	0.2053	0.1189	0.75	0.6457	2368	5402	243	729
0.1739	4.0	8932	1.8406	0.2815	0.1911	0.1092	0.7634	0.7185	1719	6051	230	742
0.163	5.0	11165	2.0274	0.2170	0.1957	0.1105	0.8570	0.7830	1064	6706	139	833
0.1481	6.0	13398	1.6407	0.2467	0.1931	0.1096	0.8107	0.7533	1369	6401	184	788
0.1334	7.0	15631	3.0800	0.1875	0.1953	0.1097	0.8868	0.8125	777	6993	110	862
0.12	8.0	17864	2.5311	0.2183	0.1962	0.1108	0.8580	0.7817	1074	6696	138	834
0.1104	9.0	20097	2.9522	0.2135	0.1935	0.1092	0.8488	0.7865	1041	6729	147	825
0.0938	10.0	22330	3.1385	0.2369	0.1919	0.1087	0.8148	0.7631	1279	6491	180	792

Framework versions

• Transformers 4.20.1
• Pytorch 1.12.0+cu102
• Datasets 2.3.2
• Tokenizers 0.12.1