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# small-5-6

This model is a fine-tuned version of [x/small-5-6/](https://huggingface.co/x/small-5-6/) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0765
- Rouge1: 33.3096
- Rouge2: 11.177
- Rougel: 26.1559
- Rougelsum: 26.1559
- Gen Len: 28.3146

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "datasets": ["xsum"], "metrics": ["rouge"], "model-index": [{"name": "small-5-6", "results": [{"task": {"type": "summarization", "name": "Summarization"}, "dataset": {"name": "xsum", "type": "xsum", "config": "default", "split": "validation", "args": "default"}, "metrics": [{"type": "rouge", "value": 33.3096, "name": "Rouge1"}]}]}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:xsum model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-xsum #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# small-5-6

This model is a fine-tuned version of x/small-5-6/ on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0765
- Rouge1: 33.3096
- Rouge2: 11.177
- Rougel: 26.1559
- Rougelsum: 26.1559
- Gen Len: 28.3146

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 3.0

### Training results



### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.12.1

# small-5-6

This model is a fine-tuned version of x/small-5-6/ on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0765
- Rouge1: 33.3096
- Rouge2: 11.177
- Rougel: 26.1559
- Rougelsum: 26.1559
- Gen Len: 28.3146 ## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-xsum #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # small-5-6

This model is a fine-tuned version of x/small-5-6/ on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0765
- Rouge1: 33.3096
- Rouge2: 11.177
- Rougel: 26.1559
- Rougelsum: 26.1559
- Gen Len: 28.3146 ## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 3.0 ### Training results ### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-xsum #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# small-5-6

This model is a fine-tuned version of x/small-5-6/ on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0765
- Rouge1: 33.3096
- Rouge2: 11.177
- Rougel: 26.1559
- Rougelsum: 26.1559
- Gen Len: 28.3146## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 3.0### Training results### Framework versions

- Transformers 4.27.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1
- Tokenizers 0.12.1