---
library_name: transformers
license: apache-2.0
base_model: sshleifer/distilbart-cnn-12-6
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: dataset_summarize
  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. -->

# dataset_summarize

This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3402
- Rouge1: 0.2705
- Rouge2: 0.0363
- Rougel: 0.1609
- Rougelsum: 0.1609
- Generated Length: 113.0

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Generated Length |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----------------:|
| No log        | 1.0   | 1    | 5.0242          | 0.2692 | 0.0362 | 0.1676 | 0.1676    | 83.5             |
| No log        | 2.0   | 2    | 4.5236          | 0.2629 | 0.0251 | 0.1431 | 0.1431    | 96.5             |
| No log        | 3.0   | 3    | 4.3402          | 0.2705 | 0.0363 | 0.1609 | 0.1609    | 113.0            |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1