---
library_name: transformers
license: apache-2.0
base_model: sshleifer/distilbart-cnn-12-6
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: distilbart-cnn-12-6-finetuned-samsum
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: validation
      args: samsum
    metrics:
    - name: Rouge1
      type: rouge
      value: 41.0557
---

<!-- 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. -->

# distilbart-cnn-12-6-finetuned-samsum

This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5040
- Rouge1: 41.0557
- Rouge2: 20.8627
- Rougel: 31.6375
- Rougelsum: 38.3023

## 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.5843        | 1.0   | 921  | 0.5095          | 40.4545 | 21.2232 | 31.2992 | 37.9698   |
| 0.4562        | 2.0   | 1842 | 0.5010          | 40.9057 | 21.0576 | 31.4701 | 38.2105   |
| 0.3938        | 3.0   | 2763 | 0.5040          | 41.0557 | 20.8627 | 31.6375 | 38.3023   |


### Framework versions

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