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# pko-t5-small-finetuned-paper-53292179

This model is a fine-tuned version of [paust/pko-t5-small](https://huggingface.co/paust/pko-t5-small) on the aihub_paper_summarization dataset.

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.0+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "datasets": ["aihub_paper_summarization"], "model-index": [{"name": "pko-t5-small-finetuned-paper-53292179", "results": []}]}
transformers pytorch tensorboard t5 text2text-generation generated_from_trainer dataset:aihub_paper_summarization license:cc-by-4.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-aihub_paper_summarization #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# pko-t5-small-finetuned-paper-53292179

This model is a fine-tuned version of paust/pko-t5-small on the aihub_paper_summarization dataset.

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.0+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2

# pko-t5-small-finetuned-paper-53292179

This model is a fine-tuned version of paust/pko-t5-small on the aihub_paper_summarization dataset. ## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3 ### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.0+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-aihub_paper_summarization #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # pko-t5-small-finetuned-paper-53292179

This model is a fine-tuned version of paust/pko-t5-small on the aihub_paper_summarization dataset. ## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3 ### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.0+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tensorboard #t5 #text2text-generation #generated_from_trainer #dataset-aihub_paper_summarization #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# pko-t5-small-finetuned-paper-53292179

This model is a fine-tuned version of paust/pko-t5-small on the aihub_paper_summarization dataset.## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: tpu
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.0+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2