finetuned_distilbert_fa_zwnj_base_ner

This model is a fine-tuned version of HooshvareLab/distilbert-fa-zwnj-base on the mixed NER dataset collected from ARMAN, PEYMA, and WikiANN. It achieves the following results on the evaluation set:

• Loss: 0.0343
• Precision: 0.9416
• Recall: 0.9549
• F1: 0.9482
• Accuracy: 0.9938

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	Precision	Recall	F1	Accuracy
0.1456	1.0	1821	0.0699	0.7847	0.8037	0.7941	0.9773
0.0551	2.0	3642	0.0456	0.8574	0.8875	0.8722	0.9858
0.0283	3.0	5463	0.0333	0.8957	0.9225	0.9089	0.9902
0.0161	4.0	7284	0.0299	0.9229	0.9374	0.9301	0.9921
0.0103	5.0	9105	0.0298	0.9314	0.9471	0.9392	0.9929
0.0069	6.0	10926	0.0323	0.9305	0.9513	0.9408	0.9930
0.0045	7.0	12747	0.0337	0.9363	0.9510	0.9436	0.9933
0.0031	8.0	14568	0.0339	0.9395	0.9526	0.9460	0.9937
0.0024	9.0	16389	0.0334	0.9392	0.9545	0.9468	0.9938
0.0017	10.0	18210	0.0343	0.9416	0.9549	0.9482	0.9938

Framework versions

• Transformers 4.21.2
• Pytorch 1.12.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1