Yepes_2e-05_31_03

This model is a fine-tuned version of microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0955
• Precision: 0.6940
• Recall: 0.5159
• F1: 0.5918
• Accuracy: 0.9824

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
• training_steps: 500

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
0.7814	1.92	25	0.2044	0.0	0.0	0.0	0.9704
0.1936	3.85	50	0.1853	0.0	0.0	0.0	0.9704
0.1651	5.77	75	0.1260	0.1667	0.0714	0.1	0.9714
0.1129	7.69	100	0.1127	0.3532	0.2354	0.2825	0.9761
0.0906	9.62	125	0.1029	0.4878	0.3175	0.3846	0.9788
0.0773	11.54	150	0.0990	0.5059	0.3386	0.4057	0.9797
0.0621	13.46	175	0.0908	0.5486	0.4180	0.4745	0.9793
0.0568	15.38	200	0.0875	0.6212	0.4339	0.5109	0.9811
0.0462	17.31	225	0.0900	0.6413	0.4683	0.5413	0.9817
0.0403	19.23	250	0.0936	0.6797	0.4603	0.5489	0.9823
0.0372	21.15	275	0.0895	0.6516	0.4947	0.5624	0.9819
0.0333	23.08	300	0.0925	0.6643	0.4974	0.5688	0.9823
0.0285	25.0	325	0.0962	0.6871	0.5053	0.5823	0.9822
0.0262	26.92	350	0.0955	0.6940	0.5159	0.5918	0.9824

Framework versions

• Transformers 4.27.4
• Pytorch 1.13.1+cu116
• Datasets 2.11.0
• Tokenizers 0.13.2