---
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
datasets:
- big_patent
metrics:
- rouge
model-index:
- name: led-base-big-patent
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: big_patent
      type: big_patent
      config: g
      split: validation
      args: g
    metrics:
    - name: Rouge1
      type: rouge
      value: 0.2658
---

<!-- 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-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: 0.2665
- Rouge1: 0.2658
- Rouge2: 0.1008
- Rougel: 0.2231
- Rougelsum: 0.2244
- Gen Len: 19.6593

## 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: 4.892476e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 108  | 0.2940          | 0.2525 | 0.0809 | 0.2062 | 0.2074    | 19.956  |
| No log        | 2.0   | 216  | 0.2595          | 0.2713 | 0.097  | 0.2233 | 0.2256    | 19.5165 |
| No log        | 3.0   | 324  | 0.2665          | 0.2658 | 0.1008 | 0.2231 | 0.2244    | 19.6593 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2