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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- farleyknight/big_patent_5_percent
metrics:
- rouge
model-index:
- name: patent-summarization-t5-base-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: 36.0843
---
<!-- 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
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