README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - null
metrics:
  - accuracy
model-index:
  - name: BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa
    results:
      - task:
          name: Text Classification
          type: text-classification
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.72

BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa

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: 0.6748
• Accuracy: 0.72

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: 1e-05
• train_batch_size: 8
• eval_batch_size: 8
• 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	Accuracy
No log	1.0	57	0.8396	0.58
No log	2.0	114	0.8608	0.58
No log	3.0	171	0.7642	0.68
No log	4.0	228	0.8196	0.64
No log	5.0	285	0.6477	0.72
No log	6.0	342	0.6861	0.72
No log	7.0	399	0.6735	0.74
No log	8.0	456	0.6516	0.72
0.6526	9.0	513	0.6707	0.72
0.6526	10.0	570	0.6748	0.72

Framework versions

• Transformers 4.10.2
• Pytorch 1.9.0+cu102
• Datasets 1.12.0
• Tokenizers 0.10.3