multilingual-Davlan/afro-xlmr-base-luganda-ner-v1

This model is a fine-tuned version of Davlan/afro-xlmr-base on the Beijuka/Multilingual_PII_NER_dataset dataset. It achieves the following results on the evaluation set:

• Loss: 0.3035
• Precision: 0.8380
• Recall: 0.8267
• F1: 0.8323
• Accuracy: 0.9570

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: 5e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: linear
• num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	261	0.3247	0.6104	0.5574	0.5827	0.9102
0.469	2.0	522	0.2311	0.7543	0.7239	0.7388	0.9381
0.469	3.0	783	0.2044	0.8267	0.7249	0.7725	0.9464
0.1333	4.0	1044	0.1721	0.8119	0.8035	0.8077	0.9577
0.1333	5.0	1305	0.2471	0.7674	0.8087	0.7875	0.9467
0.0634	6.0	1566	0.2065	0.8111	0.8304	0.8206	0.9585
0.0634	7.0	1827	0.2330	0.8451	0.8066	0.8254	0.9595
0.0328	8.0	2088	0.2440	0.8341	0.8004	0.8169	0.9580
0.0328	9.0	2349	0.2671	0.8383	0.8201	0.8291	0.9563
0.0191	10.0	2610	0.2515	0.8337	0.8294	0.8315	0.9590
0.0191	11.0	2871	0.2451	0.8477	0.8118	0.8294	0.9604
0.0095	12.0	3132	0.2637	0.8550	0.8232	0.8388	0.9624
0.0095	13.0	3393	0.2708	0.8425	0.8242	0.8332	0.9624
0.0068	14.0	3654	0.2922	0.8488	0.8128	0.8304	0.9594
0.0068	15.0	3915	0.2966	0.8303	0.8046	0.8172	0.9594

Framework versions

• Transformers 4.55.4
• Pytorch 2.8.0+cu126
• Datasets 4.0.0
• Tokenizers 0.21.4