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# results

This model is a fine-tuned version of [sshleifer/distilbart-xsum-12-1](https://huggingface.co/sshleifer/distilbart-xsum-12-1) on the ccdv/arxiv-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3066
- Rouge1: 35.6639
- Rouge2: 10.5717
- Rougel: 21.095
- Rougelsum: 31.2685
- Gen Len: 81.44

## 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
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["ccdv/arxiv-summarization"], "metrics": ["rouge"], "model-index": [{"name": "results", "results": [{"task": {"type": "summarization", "name": "Summarization"}, "dataset": {"name": "ccdv/arxiv-summarization", "type": "ccdv/arxiv-summarization", "config": "section", "split": "validation", "args": "section"}, "metrics": [{"type": "rouge", "value": 35.6639, "name": "Rouge1"}]}]}]}
transformers pytorch bart text2text-generation generated_from_trainer dataset:ccdv/arxiv-summarization license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #dataset-ccdv/arxiv-summarization #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 




# results

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-1 on the ccdv/arxiv-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3066
- Rouge1: 35.6639
- Rouge2: 10.5717
- Rougel: 21.095
- Rougelsum: 31.2685
- Gen Len: 81.44

## 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
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.13.2

# results

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-1 on the ccdv/arxiv-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3066
- Rouge1: 35.6639
- Rouge2: 10.5717
- Rougel: 21.095
- Rougelsum: 31.2685
- Gen Len: 81.44 ## 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
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #dataset-ccdv/arxiv-summarization #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 # results

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-1 on the ccdv/arxiv-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3066
- Rouge1: 35.6639
- Rouge2: 10.5717
- Rougel: 21.095
- Rougelsum: 31.2685
- Gen Len: 81.44 ## 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
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #bart #text2text-generation #generated_from_trainer #dataset-ccdv/arxiv-summarization #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
# results

This model is a fine-tuned version of sshleifer/distilbart-xsum-12-1 on the ccdv/arxiv-summarization dataset.
It achieves the following results on the evaluation set:
- Loss: 4.3066
- Rouge1: 35.6639
- Rouge2: 10.5717
- Rougel: 21.095
- Rougelsum: 31.2685
- Gen Len: 81.44## 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
- num_epochs: 3.0### Training results### Framework versions

- Transformers 4.29.0.dev0
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.13.2