
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# flan-t5-large-pubmed_qa-pqa_artificial

This model is a fine-tuned version of [google/flan-t5-large](https://huggingface.co/google/flan-t5-large) on the pubmed_qa 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results



### Framework versions

- Transformers 4.26.0
- Pytorch 1.12.1+cu113
- Datasets 2.9.0
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["pubmed_qa"], "model-index": [{"name": "flan-t5-large-pubmed_qa-pqa_artificial", "results": []}]}
transformers pytorch t5 text2text-generation generated_from_trainer dataset:pubmed_qa license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-pubmed_qa #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# flan-t5-large-pubmed_qa-pqa_artificial

This model is a fine-tuned version of google/flan-t5-large on the pubmed_qa 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results



### Framework versions

- Transformers 4.26.0
- Pytorch 1.12.1+cu113
- Datasets 2.9.0
- Tokenizers 0.13.2

# flan-t5-large-pubmed_qa-pqa_artificial

This model is a fine-tuned version of google/flan-t5-large on the pubmed_qa 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5 ### Training results ### Framework versions

- Transformers 4.26.0
- Pytorch 1.12.1+cu113
- Datasets 2.9.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-pubmed_qa #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # flan-t5-large-pubmed_qa-pqa_artificial

This model is a fine-tuned version of google/flan-t5-large on the pubmed_qa 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5 ### Training results ### Framework versions

- Transformers 4.26.0
- Pytorch 1.12.1+cu113
- Datasets 2.9.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #t5 #text2text-generation #generated_from_trainer #dataset-pubmed_qa #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# flan-t5-large-pubmed_qa-pqa_artificial

This model is a fine-tuned version of google/flan-t5-large on the pubmed_qa 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5### Training results### Framework versions

- Transformers 4.26.0
- Pytorch 1.12.1+cu113
- Datasets 2.9.0
- Tokenizers 0.13.2