electramed-small-BC2GM-ner

This model is a fine-tuned version of giacomomiolo/electramed_small_scivocab on the bc2gm_corpus dataset. It achieves the following results on the evaluation set:

• Loss: 0.0720
• Precision: 0.7652
• Recall: 0.8234
• F1: 0.7932
• Accuracy: 0.9757

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
0.085	1.0	782	0.1112	0.6147	0.7777	0.6867	0.9634
0.0901	2.0	1564	0.0825	0.7141	0.8028	0.7559	0.9720
0.0303	3.0	2346	0.0759	0.7310	0.8049	0.7662	0.9724
0.0037	4.0	3128	0.0735	0.7430	0.8168	0.7781	0.9735
0.0325	5.0	3910	0.0723	0.7571	0.8142	0.7846	0.9748
0.0582	6.0	4692	0.0701	0.7664	0.8144	0.7897	0.9759
0.0073	7.0	5474	0.0701	0.7711	0.8212	0.7953	0.9761
0.1031	8.0	6256	0.0712	0.7602	0.8258	0.7916	0.9756
0.0248	9.0	7038	0.0722	0.7691	0.8231	0.7952	0.9759
0.0136	10.0	7820	0.0720	0.7652	0.8234	0.7932	0.9757

Framework versions

• Transformers 4.22.1
• Pytorch 1.12.1+cu113
• Datasets 2.4.0
• Tokenizers 0.12.1