---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- big_patent
model-index:
- name: led-base-16384-finetuned-big_patent
  results: []
---

<!-- 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. -->

# led-base-16384-finetuned-big_patent

This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the big_patent dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5094
- Rouge2 Precision: 0.128
- Rouge2 Recall: 0.1325
- Rouge2 Fmeasure: 0.125

## 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: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 2.6657        | 0.4   | 500  | 2.6048          | 0.1211           | 0.131         | 0.121           |
| 2.6099        | 0.8   | 1000 | 2.5094          | 0.128            | 0.1325        | 0.125           |


### Framework versions

- Transformers 4.19.3
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1