---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- farleyknight/big_patent_5_percent
metrics:
- rouge
model-index:
- name: patent-summarization-allen-led-large-2022-09-20
  results:
  - task:
      name: Summarization
      type: summarization
    dataset:
      name: farleyknight/big_patent_5_percent
      type: farleyknight/big_patent_5_percent
      config: all
      split: train
      args: all
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.0
---

<!-- 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. -->

# patent-summarization-allen-led-large-2022-09-20

This model is a fine-tuned version of [allenai/led-large-16384-arxiv](https://huggingface.co/allenai/led-large-16384-arxiv) on the farleyknight/big_patent_5_percent dataset.
It achieves the following results on the evaluation set:
- Loss: 2.8233
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- Gen Len: 128.0

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 3.4766        | 0.08  | 5000  | 3.4240          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
| 3.2549        | 0.17  | 10000 | 3.2908          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
| 3.2295        | 0.25  | 15000 | 3.1862          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
| 3.1455        | 0.33  | 20000 | 3.1291          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
| 3.0526        | 0.41  | 25000 | 3.0684          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
| 3.0024        | 0.5   | 30000 | 3.0134          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
| 2.9671        | 0.58  | 35000 | 2.9696          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
| 2.9862        | 0.66  | 40000 | 2.9431          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
| 2.9168        | 0.75  | 45000 | 2.8989          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
| 2.9063        | 0.83  | 50000 | 2.8559          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
| 2.8417        | 0.91  | 55000 | 2.8398          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |
| 2.7853        | 0.99  | 60000 | 2.8240          | 0.0    | 0.0    | 0.0    | 0.0       | 512.0   |


### Framework versions

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