---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: led-base-16384-biolaysum-both-umls
  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-biolaysum-both-umls

This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1590
- Rouge1: 0.4539
- Rouge2: 0.1554
- Rougel: 0.2428
- Rougelsum: 0.2427

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

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|
| 2.2744        | 0.69  | 5000  | 2.2223          | 0.4492 | 0.1524 | 0.2419 | 0.2418    |
| 2.0397        | 1.37  | 10000 | 2.1590          | 0.4539 | 0.1554 | 0.2428 | 0.2427    |
| 1.9233        | 2.06  | 15000 | 2.1238          | 0.4554 | 0.1537 | 0.2417 | 0.2417    |
| 1.9027        | 2.75  | 20000 | 2.1115          | 0.4556 | 0.1542 | 0.2404 | 0.2404    |
| 1.78          | 3.43  | 25000 | 2.0991          | 0.4544 | 0.1523 | 0.2411 | 0.2411    |


### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1