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---
license: mit
tags:
- generated_from_trainer
datasets:
- null
metrics:
- accuracy
model-index:
- name: BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa-1
results:
- task:
name: Text Classification
type: text-classification
metrics:
- name: Accuracy
type: accuracy
value: 0.7
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext-finetuned-pubmedqa-1
This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6660
- Accuracy: 0.7
## 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 | 0.8471 | 0.58 |
| No log | 2.0 | 114 | 0.8450 | 0.58 |
| No log | 3.0 | 171 | 0.7846 | 0.58 |
| No log | 4.0 | 228 | 0.8649 | 0.58 |
| No log | 5.0 | 285 | 0.7220 | 0.68 |
| No log | 6.0 | 342 | 0.7395 | 0.66 |
| No log | 7.0 | 399 | 0.7198 | 0.72 |
| No log | 8.0 | 456 | 0.6417 | 0.72 |
| 0.7082 | 9.0 | 513 | 0.6265 | 0.74 |
| 0.7082 | 10.0 | 570 | 0.6660 | 0.7 |
### Framework versions
- Transformers 4.10.2
- Pytorch 1.9.0+cu102
- Datasets 1.12.0
- Tokenizers 0.10.3
|