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---
license: apache-2.0
tags:
- summarization
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: distilbart-cnn-12-6-ftn-multi_news
results:
- task:
name: Sequence-to-sequence Language Modeling
type: summarization
dataset:
name: multi_news
type: multi_news
args: default
metrics:
- name: Rouge1
type: rouge
value: 41.6136
- task:
type: summarization
name: Summarization
dataset:
name: multi_news
type: multi_news
config: default
split: test
metrics:
- name: ROUGE-1
type: rouge
value: 39.6512
verified: true
- name: ROUGE-2
type: rouge
value: 14.333
verified: true
- name: ROUGE-L
type: rouge
value: 21.5797
verified: true
- name: ROUGE-LSUM
type: rouge
value: 35.5793
verified: true
- name: loss
type: loss
value: 5.507579803466797
verified: true
- name: gen_len
type: gen_len
value: 132.1745
verified: true
---
<!-- 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-ftn-multi_news
This model is a fine-tuned version of [sshleifer/distilbart-cnn-12-6](https://huggingface.co/sshleifer/distilbart-cnn-12-6) on the multi_news dataset.
It achieves the following results on the evaluation set:
- Loss: 3.8143
- Rouge1: 41.6136
- Rouge2: 14.7454
- Rougel: 23.3597
- Rougelsum: 36.1973
- Gen Len: 130.874
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 1
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.8821 | 0.89 | 2000 | 3.8143 | 41.6136 | 14.7454 | 23.3597 | 36.1973 | 130.874 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
|