---
license: apache-2.0
base_model: slauw87/bart_summarisation
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bart_summarisation
  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. -->

# bart_summarisation

This model is a fine-tuned version of [slauw87/bart_summarisation](https://huggingface.co/slauw87/bart_summarisation) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9189
- Rouge1: 0.3009
- Rouge2: 0.1043
- Rougel: 0.211
- Rougelsum: 0.2108
- Gen Len: 67.473

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 313  | 1.8971          | 0.2972 | 0.1024 | 0.2092 | 0.209     | 67.394  |
| 2.2319        | 2.0   | 626  | 1.9189          | 0.3009 | 0.1043 | 0.211  | 0.2108    | 67.473  |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.1+cpu
- Datasets 2.15.0
- Tokenizers 0.15.0