xlm-roberta-base-afr-MICRO

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: 0.2268
• F1: 0.7405
• Roc Auc: 0.8537
• Accuracy: 0.6918

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
0.3224	1.0	120	0.3133	0.0	0.5	0.3627
0.317	2.0	240	0.3122	0.0	0.5	0.3627
0.2939	3.0	360	0.3043	0.0	0.5	0.3627
0.2914	4.0	480	0.3057	0.1170	0.5309	0.4046
0.2698	5.0	600	0.2474	0.5582	0.7111	0.5870
0.2265	6.0	720	0.2290	0.6752	0.7933	0.6730
0.1913	7.0	840	0.2479	0.6212	0.7753	0.5975
0.136	8.0	960	0.2088	0.6968	0.8041	0.6688
0.1243	9.0	1080	0.2222	0.7027	0.8106	0.6646
0.1106	10.0	1200	0.2118	0.7245	0.8289	0.6855
0.0829	11.0	1320	0.2289	0.6836	0.7870	0.6583
0.0835	12.0	1440	0.2250	0.6947	0.8026	0.6541
0.0801	13.0	1560	0.2180	0.7334	0.8467	0.6918
0.049	14.0	1680	0.2308	0.7055	0.8081	0.6688
0.0575	15.0	1800	0.2268	0.7405	0.8537	0.6918
0.0474	16.0	1920	0.2315	0.7158	0.8311	0.6751
0.0522	17.0	2040	0.2330	0.7064	0.8217	0.6667
0.0468	18.0	2160	0.2301	0.7265	0.8388	0.6792
0.0405	19.0	2280	0.2285	0.7259	0.8366	0.6813

Framework versions

• Transformers 4.45.1
• Pytorch 2.4.0
• Datasets 3.0.1
• Tokenizers 0.20.0