transformers pytorch t5 text2text-generation generated_from_trainer dataset:farleyknight/big_patent_5_percent license:apache-2.0 model-index autotrain_compatible text-generation-inference 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-t5-base-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: 36.0843
      name: Rouge1
---

<!-- 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-t5-base-2022-09-20

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the farleyknight/big_patent_5_percent dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9975
- Rouge1: 36.0843
- Rouge2: 12.1856
- Rougel: 25.8099
- Rougelsum: 30.1664
- Gen Len: 118.3137

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 2.2811        | 0.08  | 5000  | 2.1767          | 18.5624 | 6.8795 | 15.5361 | 16.6836   | 19.0    |
| 2.2551        | 0.17  | 10000 | 2.1327          | 19.077  | 6.8512 | 15.79   | 17.086    | 19.0    |
| 2.2818        | 0.25  | 15000 | 2.1029          | 18.8637 | 6.9233 | 15.7341 | 16.9717   | 19.0    |
| 2.1952        | 0.33  | 20000 | 2.0805          | 18.962  | 7.1157 | 15.8297 | 17.0333   | 19.0    |
| 2.157         | 0.41  | 25000 | 2.0641          | 19.1418 | 7.315  | 16.05   | 17.2551   | 19.0    |
| 2.1775        | 0.5   | 30000 | 2.0452          | 19.2387 | 7.3193 | 16.0852 | 17.3563   | 19.0    |
| 2.1376        | 0.58  | 35000 | 2.0308          | 19.291  | 7.363  | 16.1243 | 17.4151   | 19.0    |
| 2.1853        | 0.66  | 40000 | 2.0207          | 19.2808 | 7.4671 | 16.1593 | 17.3836   | 19.0    |
| 2.1416        | 0.75  | 45000 | 2.0113          | 19.0414 | 7.3335 | 15.9747 | 17.1899   | 19.0    |
| 2.1245        | 0.83  | 50000 | 2.0055          | 19.1445 | 7.3715 | 16.0166 | 17.2621   | 19.0    |
| 2.133         | 0.91  | 55000 | 1.9997          | 19.3033 | 7.4821 | 16.1413 | 17.3949   | 19.0    |
| 2.1191        | 0.99  | 60000 | 1.9973          | 19.4044 | 7.5483 | 16.2429 | 17.488    | 19.0    |


### Framework versions

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