metadata

license: mit
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: tmvar_2e-05_250
    results: []

tmvar_2e-05_250

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: 0.0128
Precision: 0.8756
Recall: 0.9135
F1: 0.8942
Accuracy: 0.9974

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
0.486	1.0	25	0.0910	0.0	0.0	0.0	0.9858
0.0765	2.0	50	0.0410	0.6267	0.2541	0.3615	0.9889
0.0399	3.0	75	0.0230	0.6513	0.6865	0.6684	0.9941
0.0254	4.0	100	0.0176	0.7170	0.8216	0.7657	0.9957
0.0139	5.0	125	0.0129	0.8710	0.8757	0.8733	0.9968
0.0078	6.0	150	0.0107	0.9027	0.9027	0.9027	0.9974
0.0057	7.0	175	0.0110	0.8763	0.9189	0.8971	0.9975
0.0042	8.0	200	0.0113	0.8718	0.9189	0.8947	0.9971
0.003	9.0	225	0.0118	0.8802	0.9135	0.8966	0.9974
0.0022	10.0	250	0.0121	0.8877	0.8973	0.8925	0.9972
0.0019	11.0	275	0.0126	0.8756	0.9135	0.8942	0.9972
0.0016	12.0	300	0.0126	0.8802	0.9135	0.8966	0.9974
0.0015	13.0	325	0.0129	0.8769	0.9243	0.9	0.9974
0.0013	14.0	350	0.0128	0.8756	0.9135	0.8942	0.9974

Framework versions

Transformers 4.27.4
Pytorch 1.13.1+cu116
Datasets 2.11.0
Tokenizers 0.13.2