---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- multi_news
model-index:
- name: summarise_v4
  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. -->

# summarise_v4

This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the multi_news dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5264
- Rouge2 Precision: 0.1349
- Rouge2 Recall: 0.1187
- Rouge2 Fmeasure: 0.1227

## 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
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
| 2.9616        | 0.08  | 10   | 2.8008          | 0.0552           | 0.1944        | 0.0844          |
| 2.7112        | 0.16  | 20   | 2.7017          | 0.1099           | 0.1212        | 0.1078          |
| 2.6842        | 0.24  | 30   | 2.6653          | 0.119            | 0.1252        | 0.1157          |
| 2.4638        | 0.32  | 40   | 2.6306          | 0.1386           | 0.1153        | 0.1222          |
| 2.646         | 0.4   | 50   | 2.6099          | 0.1449           | 0.1095        | 0.122           |
| 2.5128        | 0.48  | 60   | 2.5945          | 0.1259           | 0.1484        | 0.1313          |
| 2.6737        | 0.56  | 70   | 2.5832          | 0.1192           | 0.1252        | 0.118           |
| 2.614         | 0.64  | 80   | 2.5616          | 0.1288           | 0.1179        | 0.1193          |
| 2.4643        | 0.72  | 90   | 2.5612          | 0.1371           | 0.1227        | 0.124           |
| 2.3164        | 0.8   | 100  | 2.5606          | 0.1372           | 0.1177        | 0.1223          |
| 2.4514        | 0.88  | 110  | 2.5339          | 0.1412           | 0.1276        | 0.128           |
| 2.8113        | 0.96  | 120  | 2.5264          | 0.1349           | 0.1187        | 0.1227          |


### Framework versions

- Transformers 4.21.3
- Pytorch 1.12.1+cu113
- Datasets 2.6.2.dev0
- Tokenizers 0.12.1