electramed-small-ADE-DRUG-EFFECT-ner

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

• Loss: 0.1630
• Precision: 0.7745
• Recall: 0.6555
• F1: 0.7101
• Accuracy: 0.9310

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
0.4498	1.0	336	0.3042	0.5423	0.6295	0.5826	0.9114
0.2572	2.0	672	0.2146	0.7596	0.6194	0.6824	0.9276
0.1542	3.0	1008	0.1894	0.7806	0.6168	0.6891	0.9299
0.1525	4.0	1344	0.1771	0.7832	0.625	0.6952	0.9309
0.1871	5.0	1680	0.1723	0.7271	0.6920	0.7091	0.9304
0.1425	6.0	2016	0.1683	0.7300	0.6979	0.7136	0.9297
0.1638	7.0	2352	0.1654	0.7432	0.6771	0.7086	0.9306
0.1592	8.0	2688	0.1635	0.7613	0.6585	0.7062	0.9305
0.1882	9.0	3024	0.1625	0.7858	0.6373	0.7038	0.9309
0.1339	10.0	3360	0.1630	0.7745	0.6555	0.7101	0.9310

Framework versions

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