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# small-3-6

This model is a fine-tuned version of [cnn/small-3-6/](https://huggingface.co/cnn/small-3-6/) on the cnn_dailymail 3.0.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7320
- Rouge1: 38.5733
- Rouge2: 16.7984
- Rougel: 27.1527
- Rougelsum: 35.793
- Gen Len: 78.1339

## 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": ["cnn_dailymail"], "metrics": ["rouge"], "model-index": [{"name": "small-3-6", "results": [{"task": {"type": "summarization", "name": "Summarization"}, "dataset": {"name": "cnn_dailymail 3.0.0", "type": "cnn_dailymail", "config": "3.0.0", "split": "validation", "args": "3.0.0"}, "metrics": [{"type": "rouge", "value": 38.5733, "name": "Rouge1"}]}]}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:cnn_dailymail model-index autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-cnn_dailymail #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# small-3-6

This model is a fine-tuned version of cnn/small-3-6/ on the cnn_dailymail 3.0.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7320
- Rouge1: 38.5733
- Rouge2: 16.7984
- Rougel: 27.1527
- Rougelsum: 35.793
- Gen Len: 78.1339

## 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-3-6

This model is a fine-tuned version of cnn/small-3-6/ on the cnn_dailymail 3.0.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7320
- Rouge1: 38.5733
- Rouge2: 16.7984
- Rougel: 27.1527
- Rougelsum: 35.793
- Gen Len: 78.1339 ## 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-cnn_dailymail #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # small-3-6

This model is a fine-tuned version of cnn/small-3-6/ on the cnn_dailymail 3.0.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7320
- Rouge1: 38.5733
- Rouge2: 16.7984
- Rougel: 27.1527
- Rougelsum: 35.793
- Gen Len: 78.1339 ## 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-cnn_dailymail #model-index #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# small-3-6

This model is a fine-tuned version of cnn/small-3-6/ on the cnn_dailymail 3.0.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7320
- Rouge1: 38.5733
- Rouge2: 16.7984
- Rougel: 27.1527
- Rougelsum: 35.793
- Gen Len: 78.1339## 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