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# bart-large-cnn-finetuned-multi-news1

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the multi_news dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0858
- Rouge1: 42.1215
- Rouge2: 14.9986
- Rougel: 23.4737
- Rougelsum: 36.4212
- Gen Len: 133.703

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.1984        | 1.0   | 750  | 2.0858          | 42.1215 | 14.9986 | 23.4737 | 36.4212   | 133.703 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["multi_news"], "metrics": ["rouge"], "model-index": [{"name": "bart-large-cnn-finetuned-multi-news1", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "multi_news", "type": "multi_news", "args": "default"}, "metrics": [{"type": "rouge", "value": 42.1215, "name": "Rouge1"}]}]}]}
transformers pytorch tensorboard bart text2text-generation generated_from_trainer dataset:multi_news license:mit model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #dataset-multi_news #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 

bart-large-cnn-finetuned-multi-news1
====================================


This model is a fine-tuned version of facebook/bart-large-cnn on the multi\_news dataset.
It achieves the following results on the evaluation set:


* Loss: 2.0858
* Rouge1: 42.1215
* Rouge2: 14.9986
* Rougel: 23.4737
* Rougelsum: 36.4212
* Gen Len: 133.703


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
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1


### Training results



### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #dataset-multi_news #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1 ### Training results ### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6
passage: TAGS
#transformers #pytorch #tensorboard #bart #text2text-generation #generated_from_trainer #dataset-multi_news #license-mit #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 2e-05
* train\_batch\_size: 4
* eval\_batch\_size: 4
* seed: 42
* gradient\_accumulation\_steps: 4
* total\_train\_batch\_size: 16
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 1### Training results### Framework versions


* Transformers 4.18.0
* Pytorch 1.10.0+cu111
* Datasets 2.0.0
* Tokenizers 0.11.6