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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- pub_med_summarization_dataset
metrics:
- rouge
model-index:
- name: bigbird-pegasus-large-bigpatent-finetuned-pubMed
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: pub_med_summarization_dataset
type: pub_med_summarization_dataset
args: document
metrics:
- name: Rouge1
type: rouge
value: 45.0851
---
<!-- 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. -->
# bigbird-pegasus-large-bigpatent-finetuned-pubMed
This model is a fine-tuned version of [google/bigbird-pegasus-large-bigpatent](https://huggingface.co/google/bigbird-pegasus-large-bigpatent) on the pub_med_summarization_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5403
- Rouge1: 45.0851
- Rouge2: 19.5488
- Rougel: 27.391
- Rougelsum: 41.112
- Gen Len: 231.608
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.1198 | 1.0 | 500 | 1.6285 | 43.0579 | 18.1792 | 26.421 | 39.0769 | 214.924 |
| 1.6939 | 2.0 | 1000 | 1.5696 | 44.0679 | 18.9331 | 26.84 | 40.0684 | 222.814 |
| 1.6195 | 3.0 | 1500 | 1.5506 | 44.7352 | 19.3532 | 27.2418 | 40.7454 | 229.396 |
| 1.5798 | 4.0 | 2000 | 1.5403 | 45.0415 | 19.5019 | 27.2969 | 40.951 | 231.044 |
| 1.5592 | 5.0 | 2500 | 1.5403 | 45.0851 | 19.5488 | 27.391 | 41.112 | 231.608 |
### Framework versions
- Transformers 4.17.0
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.11.6
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