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---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: bart-large-cnn-finetuned-CNN-ML
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: cnn_dailymail
type: cnn_dailymail
config: 3.0.0
split: test
args: 3.0.0
metrics:
- name: Rouge1
type: rouge
value: 44.4382
---
<!-- 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. -->
# bart-large-cnn-finetuned-CNN-ML
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1137
- Rouge1: 44.4382
- Rouge2: 20.686
- Rougel: 29.9355
- Rougelsum: 41.4113
- Gen Len: 93.846
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.0341 | 1.0 | 1000 | 1.5412 | 43.0331 | 20.1656 | 29.6298 | 39.9858 | 83.22 |
| 0.6416 | 2.0 | 2000 | 1.8461 | 44.2294 | 20.5043 | 29.6298 | 41.1457 | 93.366 |
| 0.3766 | 3.0 | 3000 | 2.1137 | 44.4382 | 20.686 | 29.9355 | 41.4113 | 93.846 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
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