abduaziz/roberta-ner-uzbek

Uzbek NER model

This model is a fine-tuned version of FacebookAI/xlm-roberta-large on the Uzbek Ner dataset. It achieves the following results on the evaluation set:

• Loss: 0.1421
• Precision: 0.6071
• Recall: 0.6482
• F1: 0.6270
• Accuracy: 0.9486

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: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
• lr_scheduler_type: cosine
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 3
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.1671	0.5758	150	0.1632	0.5260	0.6425	0.5785	0.9402
0.1453	1.1497	300	0.1481	0.5935	0.6191	0.6061	0.9467
0.134	1.7255	450	0.1449	0.5936	0.6216	0.6073	0.9480
0.1273	2.2994	600	0.1413	0.6217	0.6262	0.6239	0.9493
0.1258	2.8752	750	0.1421	0.6071	0.6482	0.6270	0.9486

Framework versions

• Transformers 4.47.0
• Pytorch 2.1.1+cu121
• Datasets 3.2.0
• Tokenizers 0.21.0