---
library_name: transformers
license: bsd-3-clause
base_model: pszemraj/led-base-book-summary
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: LED-cnn-dataset-summarization
  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-cnn-dataset-summarization

This model is a fine-tuned version of [pszemraj/led-base-book-summary](https://huggingface.co/pszemraj/led-base-book-summary) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0098
- Rouge1: 0.4061
- Rouge2: 0.1676
- Rougel: 0.2695
- Rougelsum: 0.3756
- Gen Len: 79.036

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 250  | 1.8883          | 0.4074 | 0.1733 | 0.2733 | 0.3741    | 81.696  |
| 1.9196        | 2.0   | 500  | 1.8782          | 0.4105 | 0.1738 | 0.2735 | 0.3789    | 85.312  |
| 1.9196        | 3.0   | 750  | 1.8763          | 0.408  | 0.1734 | 0.2747 | 0.3754    | 84.348  |
| 1.4188        | 4.0   | 1000 | 1.9043          | 0.4086 | 0.1716 | 0.273  | 0.3795    | 79.842  |
| 1.4188        | 5.0   | 1250 | 1.9344          | 0.4084 | 0.1686 | 0.2713 | 0.377     | 79.926  |
| 1.168         | 6.0   | 1500 | 1.9623          | 0.4121 | 0.1733 | 0.2749 | 0.3813    | 77.228  |
| 1.168         | 7.0   | 1750 | 2.0004          | 0.4092 | 0.1711 | 0.273  | 0.3794    | 77.102  |
| 1.0279        | 8.0   | 2000 | 2.0098          | 0.4061 | 0.1676 | 0.2695 | 0.3756    | 79.036  |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1