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# long-t5-tglobal-base-biolaysum-elife-baseline

This model is a fine-tuned version of [google/long-t5-tglobal-base](https://huggingface.co/google/long-t5-tglobal-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.0290
- Rouge2: 0.0048
- Rougel: 0.0253
- Rougelsum: 0.0252

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["rouge"], "model-index": [{"name": "long-t5-tglobal-base-biolaysum-elife-baseline", "results": []}]}
transformers pytorch longt5 text2text-generation generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #longt5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 




# long-t5-tglobal-base-biolaysum-elife-baseline

This model is a fine-tuned version of google/long-t5-tglobal-base on the None dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.0290
- Rouge2: 0.0048
- Rougel: 0.0253
- Rougelsum: 0.0252

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results



### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1

# long-t5-tglobal-base-biolaysum-elife-baseline

This model is a fine-tuned version of google/long-t5-tglobal-base on the None dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.0290
- Rouge2: 0.0048
- Rougel: 0.0253
- Rougelsum: 0.0252 ## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #longt5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # long-t5-tglobal-base-biolaysum-elife-baseline

This model is a fine-tuned version of google/long-t5-tglobal-base on the None dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.0290
- Rouge2: 0.0048
- Rougel: 0.0253
- Rougelsum: 0.0252 ## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP ### Training results ### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #longt5 #text2text-generation #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# long-t5-tglobal-base-biolaysum-elife-baseline

This model is a fine-tuned version of google/long-t5-tglobal-base on the None dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Rouge1: 0.0290
- Rouge2: 0.0048
- Rougel: 0.0253
- Rougelsum: 0.0252## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP### Training results### Framework versions

- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1