---
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
datasets:
- scientific_papers
model-index:
- name: allenai/led-base-16384
  results: []
---

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# allenai/led-base-16384

This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the scientific_papers dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7667
- Rouge2 Precision: 0.15
- Rouge2 Recall: 0.0913
- Rouge2 Fmeasure: 0.1075

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 2.8931        | 0.32  | 10   | 2.9211          | 0.1243           | 0.1206        | 0.1119          |
| 3.0026        | 0.64  | 20   | 2.8150          | 0.1589           | 0.1102        | 0.1241          |
| 2.7651        | 0.96  | 30   | 2.7667          | 0.15             | 0.0913        | 0.1075          |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.15.0