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# results

This model is a fine-tuned version of [sshleifer/distilbart-xsum-12-3](https://huggingface.co/sshleifer/distilbart-xsum-12-3) on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 7.4393
- Rouge1: 16.9502
- Rouge2: 1.9608
- Rougel: 15.0983
- Rougelsum: 16.9502
- Gen Len: 19.3333

## 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: 5e-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
- label_smoothing_factor: 0.1

### Training results



### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["wiki_lingua"], "metrics": ["rouge"], "model-index": [{"name": "results", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "wiki_lingua", "type": "wiki_lingua", "config": "english", "split": "train[:10]", "args": "english"}, "metrics": [{"type": "rouge", "value": 16.9502, "name": "Rouge1"}]}]}]}
transformers pytorch bart text2text-generation generated_from_trainer dataset:wiki_lingua license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #dataset-wiki_lingua #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 




# results

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 7.4393
- Rouge1: 16.9502
- Rouge2: 1.9608
- Rougel: 15.0983
- Rougelsum: 16.9502
- Gen Len: 19.3333

## 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: 5e-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
- label_smoothing_factor: 0.1

### Training results



### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3

# results

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 7.4393
- Rouge1: 16.9502
- Rouge2: 1.9608
- Rougel: 15.0983
- Rougelsum: 16.9502
- Gen Len: 19.3333 ## 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: 5e-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
- label_smoothing_factor: 0.1 ### Training results ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #dataset-wiki_lingua #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 # results

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 7.4393
- Rouge1: 16.9502
- Rouge2: 1.9608
- Rougel: 15.0983
- Rougelsum: 16.9502
- Gen Len: 19.3333 ## 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: 5e-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
- label_smoothing_factor: 0.1 ### Training results ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #dataset-wiki_lingua #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
# results

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on the wiki_lingua dataset.
It achieves the following results on the evaluation set:
- Loss: 7.4393
- Rouge1: 16.9502
- Rouge2: 1.9608
- Rougel: 15.0983
- Rougelsum: 16.9502
- Gen Len: 19.3333## 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: 5e-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
- label_smoothing_factor: 0.1### Training results### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.3