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---
tags:
- generated_from_trainer
datasets:
- epi_classify4_gard
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: results
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: epi_classify4_gard
type: epi_classify4_gard
args: default
metrics:
- name: Precision
type: precision
value: 0.875
- name: Recall
type: recall
value: 0.9032258064516129
- name: F1
type: f1
value: 0.8888888888888888
- name: Accuracy
type: accuracy
value: 0.986
---
<!-- 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. -->
# results
This model is a fine-tuned version of [dmis-lab/biobert-base-cased-v1.2](https://huggingface.co/dmis-lab/biobert-base-cased-v1.2) on the epi_classify4_gard dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0541
- Precision: 0.875
- Recall: 0.9032
- F1: 0.8889
- Accuracy: 0.986
## 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: 3e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4.0
### Training results
### Framework versions
- Transformers 4.12.5
- Pytorch 1.9.0+cu102
- Datasets 1.12.1
- Tokenizers 0.10.3
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