transformers pytorch tensorboard safetensors bart text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: distilbart-cnn-12-6-summarization_final_labeled_data
  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. -->

# distilbart-cnn-12-6-summarization_final_labeled_data

This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0858
- Rouge1: 76.5974
- Rouge2: 66.1659
- Rougel: 71.9284
- Rougelsum: 75.2459
- Gen Len: 122.5

## 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: 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 99   | 0.2852          | 61.0841 | 45.81   | 52.9835 | 59.0452   | 116.92  |
| No log        | 2.0   | 198  | 0.1547          | 71.534  | 59.9905 | 66.4697 | 70.5213   | 117.56  |
| No log        | 3.0   | 297  | 0.1100          | 71.6464 | 59.0112 | 67.3835 | 70.5206   | 117.24  |
| No log        | 4.0   | 396  | 0.0960          | 77.9213 | 67.6116 | 73.7888 | 76.8473   | 123.62  |
| No log        | 5.0   | 495  | 0.0858          | 76.5974 | 66.1659 | 71.9284 | 75.2459   | 122.5   |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
