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# fine-tune-Pegasus

This model is a fine-tuned version of [google/pegasus-large](https://huggingface.co/google/pegasus-large) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3242
- Rouge1: 17.993
- Rouge2: 2.9392
- Rougel: 12.313
- Rougelsum: 13.3091
- Gen Len: 67.0552

## 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: 6.35e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.1
- Datasets 1.17.0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "datasets": ["xsum"], "metrics": ["rouge"], "model-index": [{"name": "fine-tune-Pegasus", "results": [{"task": {"type": "text2text-generation", "name": "Sequence-to-sequence Language Modeling"}, "dataset": {"name": "xsum", "type": "xsum", "args": "default"}, "metrics": [{"type": "rouge", "value": 17.993, "name": "Rouge1"}]}]}]}
transformers pytorch pegasus text2text-generation generated_from_trainer dataset:xsum model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #pegasus #text2text-generation #generated_from_trainer #dataset-xsum #model-index #autotrain_compatible #endpoints_compatible #region-us 




# fine-tune-Pegasus

This model is a fine-tuned version of google/pegasus-large on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3242
- Rouge1: 17.993
- Rouge2: 2.9392
- Rougel: 12.313
- Rougelsum: 13.3091
- Gen Len: 67.0552

## 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: 6.35e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.1
- Datasets 1.17.0
- Tokenizers 0.10.3

# fine-tune-Pegasus

This model is a fine-tuned version of google/pegasus-large on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3242
- Rouge1: 17.993
- Rouge2: 2.9392
- Rougel: 12.313
- Rougelsum: 13.3091
- Gen Len: 67.0552 ## 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: 6.35e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 1.0
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.1
- Datasets 1.17.0
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #pegasus #text2text-generation #generated_from_trainer #dataset-xsum #model-index #autotrain_compatible #endpoints_compatible #region-us 
 # fine-tune-Pegasus

This model is a fine-tuned version of google/pegasus-large on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3242
- Rouge1: 17.993
- Rouge2: 2.9392
- Rougel: 12.313
- Rougelsum: 13.3091
- Gen Len: 67.0552 ## 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: 6.35e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 1.0
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.1
- Datasets 1.17.0
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #pegasus #text2text-generation #generated_from_trainer #dataset-xsum #model-index #autotrain_compatible #endpoints_compatible #region-us 
# fine-tune-Pegasus

This model is a fine-tuned version of google/pegasus-large on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3242
- Rouge1: 17.993
- Rouge2: 2.9392
- Rougel: 12.313
- Rougelsum: 13.3091
- Gen Len: 67.0552## 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: 6.35e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 500
- num_epochs: 1.0
- mixed_precision_training: Native AMP### Training results### Framework versions

- Transformers 4.16.2
- Pytorch 1.10.1
- Datasets 1.17.0
- Tokenizers 0.10.3