transformers pytorch bigbird_pegasus text2text-generation generated_from_trainer dataset:farleyknight/big_patent_5_percent license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- farleyknight/big_patent_5_percent
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: patent-summarization-google-bigbird-pegasus-large-arxiv-2022-09-20
  results:
  - task:
      type: summarization
      name: Summarization
    dataset:
      name: farleyknight/big_patent_5_percent
      type: farleyknight/big_patent_5_percent
      config: all
      split: train
      args: all
    metrics:
    - type: rouge
      value: 37.3764
      name: Rouge1
---

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# patent-summarization-google-bigbird-pegasus-large-arxiv-2022-09-20

This model is a fine-tuned version of [google/bigbird-pegasus-large-arxiv](https://huggingface.co/google/bigbird-pegasus-large-arxiv) on the farleyknight/big_patent_5_percent dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2617
- Rouge1: 37.3764
- Rouge2: 13.2442
- Rougel: 26.011
- Rougelsum: 31.0145
- Gen Len: 113.8789

## 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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len  |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:--------:|
| 2.6121        | 0.08  | 5000  | 2.5652          | 35.0673 | 12.0073 | 24.5471 | 28.9315   | 119.9866 |
| 2.5182        | 0.17  | 10000 | 2.4797          | 34.6909 | 11.6432 | 24.87   | 28.1543   | 119.2043 |
| 2.5102        | 0.25  | 15000 | 2.4238          | 35.8574 | 12.2402 | 25.0712 | 29.5607   | 115.2890 |
| 2.4292        | 0.33  | 20000 | 2.3869          | 36.0133 | 12.2453 | 25.4039 | 29.483    | 112.5920 |
| 2.3678        | 0.41  | 25000 | 2.3594          | 35.238  | 11.6833 | 25.0449 | 28.3313   | 119.1739 |
| 2.3511        | 0.5   | 30000 | 2.3326          | 36.7755 | 12.8394 | 25.7218 | 30.2594   | 110.5819 |
| 2.3334        | 0.58  | 35000 | 2.3125          | 36.6317 | 12.7493 | 25.5388 | 30.094    | 115.5998 |
| 2.3833        | 0.66  | 40000 | 2.2943          | 37.1219 | 13.1564 | 25.7571 | 30.8666   | 113.8222 |
| 2.341         | 0.75  | 45000 | 2.2813          | 36.4962 | 12.6225 | 25.6904 | 29.9741   | 115.9845 |
| 2.3179        | 0.83  | 50000 | 2.2725          | 37.3535 | 13.1596 | 25.7385 | 31.056    | 117.7754 |
| 2.3164        | 0.91  | 55000 | 2.2654          | 36.9191 | 12.9316 | 25.7586 | 30.4691   | 116.1670 |
| 2.3046        | 0.99  | 60000 | 2.2618          | 37.3992 | 13.2731 | 26.0327 | 31.0338   | 114.5195 |


### Framework versions

- Transformers 4.23.0.dev0
- Pytorch 1.12.0
- Datasets 2.4.0
- Tokenizers 0.12.1
