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# ja-t5-base-summary

This model is a fine-tuned version of [sonoisa/t5-base-japanese](https://huggingface.co/sonoisa/t5-base-japanese) on an news&summary dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8166
- Rouge1: 22.9414
- Rouge2: 6.7422
- Rougel: 22.3874
- Rougelsum: 22.3773
- Gen Len: 57.5169

## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results



### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.12.1

{"license": "cc-by-sa-4.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "ja-t5-base-summary", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer license:cc-by-sa-4.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# ja-t5-base-summary

This model is a fine-tuned version of sonoisa/t5-base-japanese on an news&summary dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8166
- Rouge1: 22.9414
- Rouge2: 6.7422
- Rougel: 22.3874
- Rougelsum: 22.3773
- Gen Len: 57.5169

## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results



### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.12.1

# ja-t5-base-summary

This model is a fine-tuned version of sonoisa/t5-base-japanese on an news&summary dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8166
- Rouge1: 22.9414
- Rouge2: 6.7422
- Rougel: 22.3874
- Rougelsum: 22.3773
- Gen Len: 57.5169 ## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0 ### Training results ### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # ja-t5-base-summary

This model is a fine-tuned version of sonoisa/t5-base-japanese on an news&summary dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8166
- Rouge1: 22.9414
- Rouge2: 6.7422
- Rougel: 22.3874
- Rougelsum: 22.3773
- Gen Len: 57.5169 ## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0 ### Training results ### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #license-cc-by-sa-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# ja-t5-base-summary

This model is a fine-tuned version of sonoisa/t5-base-japanese on an news&summary dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8166
- Rouge1: 22.9414
- Rouge2: 6.7422
- Rougel: 22.3874
- Rougelsum: 22.3773
- Gen Len: 57.5169## 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: 6
- eval_batch_size: 6
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0### Training results### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 1.13.1+cu117
- Datasets 2.11.0
- Tokenizers 0.12.1