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---
license: mit
tags:
- generated_from_trainer
model-index:
- name: med_masked_pubmed_articles_biogpt
results: []
---
<!-- 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. -->
# med_masked_pubmed_articles_biogpt
This model is a fine-tuned version of [microsoft/biogpt](https://huggingface.co/microsoft/biogpt) on a med_masked_pubmed_articles dataset.
It achieves the following results on the evaluation set:
- Loss: 3.1952
- Rouge2 Precision: 0.7072
- Rouge2 Recall: 0.7001
- Rouge2 Fmeasure: 0.7025
## 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
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 3.1392 | 1.0 | 7914 | 3.0945 | 0.7075 | 0.7001 | 0.7026 |
| 2.927 | 2.0 | 15828 | 3.0705 | 0.7074 | 0.7001 | 0.7026 |
| 2.8558 | 3.0 | 23742 | 3.0877 | 0.7073 | 0.7001 | 0.7025 |
| 2.7035 | 4.0 | 31656 | 3.1354 | 0.7073 | 0.7001 | 0.7026 |
| 2.6209 | 5.0 | 39570 | 3.1952 | 0.7072 | 0.7001 | 0.7025 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu116
- Datasets 2.9.0
- Tokenizers 0.13.2
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