README.md

metadata

license: mit
tags:
  - generated_from_trainer
metrics:
  - precision
  - recall
  - f1
  - accuracy
model-index:
  - name: tmvar_5e-05_250
    results: []

tmvar_5e-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: 0.0104
• Precision: 0.8718
• Recall: 0.9189
• F1: 0.8947
• Accuracy: 0.9977

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: 5e-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
0.2897	1.0	25	0.0896	0.0	0.0	0.0	0.9858
0.0759	2.0	50	0.0302	0.5522	0.4	0.4639	0.9898
0.0347	3.0	75	0.0175	0.6789	0.6973	0.688	0.9945
0.0174	4.0	100	0.0133	0.76	0.8216	0.7896	0.9962
0.0084	5.0	125	0.0125	0.805	0.8703	0.8364	0.9967
0.0048	6.0	150	0.0090	0.8859	0.8811	0.8835	0.9977
0.0025	7.0	175	0.0097	0.8382	0.9243	0.8792	0.9977
0.0017	8.0	200	0.0089	0.8529	0.9405	0.8946	0.9980
0.0015	9.0	225	0.0099	0.8357	0.9351	0.8827	0.9979
0.0012	10.0	250	0.0104	0.8522	0.9351	0.8918	0.9979
0.0011	11.0	275	0.0104	0.8798	0.8703	0.875	0.9972
0.0009	12.0	300	0.0098	0.8718	0.9189	0.8947	0.9977
0.0007	13.0	325	0.0100	0.8718	0.9189	0.8947	0.9977
0.0006	14.0	350	0.0104	0.8718	0.9189	0.8947	0.9977

Framework versions

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