detect-femicide-news-xlmr

This model is a fine-tuned version of xlm-roberta-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.0161
• Accuracy: 0.9973
• Precision Neg: 0.9975
• Precision Pos: 0.9967
• Recall Neg: 0.9988
• Recall Pos: 0.9933
• F1 Score Neg: 0.9981
• F1 Score Pos: 0.9950

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: 1e-05
• train_batch_size: 128
• eval_batch_size: 8
• seed: 1996
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 6

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	Precision Neg	Precision Pos	Recall Neg	Recall Pos	F1 Score Neg	F1 Score Pos
0.2758	1.0	204	0.1001	0.9718	0.9741	0.9654	0.9875	0.93	0.9808	0.9474
0.0782	2.0	408	0.0505	0.9809	0.9839	0.9729	0.99	0.9567	0.9869	0.9647
0.0501	3.0	612	0.0272	0.9927	0.9962	0.9834	0.9938	0.99	0.9950	0.9867
0.0389	4.0	816	0.0201	0.9945	0.9938	0.9966	0.9988	0.9833	0.9963	0.9899
0.031	5.0	1020	0.0175	0.9964	0.9963	0.9966	0.9988	0.99	0.9975	0.9933
0.0235	6.0	1224	0.0161	0.9973	0.9975	0.9967	0.9988	0.9933	0.9981	0.9950

Framework versions

• Transformers 4.16.2
• Pytorch 1.10.2+cu113
• Datasets 1.18.3
• Tokenizers 0.11.0