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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-fb-bart-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: 39.4401
---
<!-- 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-fb-bart-base-2022-09-20
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the farleyknight/big_patent_5_percent dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4088
- Rouge1: 39.4401
- Rouge2: 14.2445
- Rougel: 26.2701
- Rougelsum: 33.7535
- Gen Len: 78.9702
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 3.0567 | 0.08 | 5000 | 2.8864 | 18.9387 | 7.1014 | 15.4506 | 16.8377 | 19.9979 |
| 2.9285 | 0.17 | 10000 | 2.7800 | 19.8983 | 7.3258 | 16.0823 | 17.7019 | 20.0 |
| 2.9252 | 0.25 | 15000 | 2.7080 | 19.6623 | 7.4627 | 16.0153 | 17.4485 | 20.0 |
| 2.8123 | 0.33 | 20000 | 2.6585 | 19.7414 | 7.5251 | 15.8166 | 17.4668 | 20.0 |
| 2.7117 | 0.41 | 25000 | 2.6070 | 19.7661 | 7.7193 | 16.2795 | 17.7884 | 20.0 |
| 2.7131 | 0.5 | 30000 | 2.5616 | 19.6706 | 7.4229 | 15.7998 | 17.4324 | 20.0 |
| 2.6373 | 0.58 | 35000 | 2.5250 | 20.0155 | 7.6811 | 16.1231 | 17.7578 | 20.0 |
| 2.6785 | 0.66 | 40000 | 2.4977 | 20.0974 | 7.9578 | 16.543 | 18.0242 | 20.0 |
| 2.6265 | 0.75 | 45000 | 2.4701 | 19.994 | 7.9114 | 16.3501 | 17.8786 | 20.0 |
| 2.5833 | 0.83 | 50000 | 2.4441 | 19.9981 | 7.934 | 16.3033 | 17.8674 | 20.0 |
| 2.5579 | 0.91 | 55000 | 2.4251 | 20.0544 | 7.8966 | 16.3889 | 17.9491 | 20.0 |
| 2.5242 | 0.99 | 60000 | 2.4097 | 20.1093 | 8.0572 | 16.4935 | 17.9823 | 20.0 |
### Framework versions
- Transformers 4.23.0.dev0
- Pytorch 1.12.0
- Datasets 2.4.0
- Tokenizers 0.12.1
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