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# QAll-Flan-xl

This model is a fine-tuned version of [google/flan-t5-xl](https://huggingface.co/google/flan-t5-xl) on an unknown dataset.
It achieves the following results on the evaluation set:


## 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:
- optimizer: None
- training_precision: float32

### Training results



### Framework versions

- Transformers 4.25.1
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "pipeline_tag": "text2text-generation", "widget": [{"text": "Answer the question based on the context.\nContext: The Review of Politics was founded in 1939 by Gurian, modeled after German Catholic journals. It quickly emerged as part of an international Catholic intellectual revival, offering an alternative vision to positivist philosophy. For 44 years, the Review was edited by Gurian, Matthew Fitzsimons, Frederick Crosson, and Thomas Stritch. Intellectual leaders included Gurian, Jacques Maritain, Frank O'Malley, Leo Richard Ward, F. A. Hermens, and John U. Nef. It became a major forum for political ideas and modern political concerns, especially from a Catholic and scholastic tradition.\nQuestion: Who was the last editor of the Review of Political Science?", "example_title": "Question Answering"}, {"text": "Generate a question based on the context and the answer.\nContext: The Review of Politics was founded in 1939 by Gurian, modeled after German Catholic journals. It quickly emerged as part of an international Catholic intellectual revival, offering an alternative vision to positivist philosophy. For 44 years, the Review was edited by Gurian, Matthew Fitzsimons, Frederick Crosson, and Thomas Stritch. Intellectual leaders included Gurian, Jacques Maritain, Frank O'Malley, Leo Richard Ward, F. A. Hermens, and John U. Nef. It became a major forum for political ideas and modern political concerns, especially from a Catholic and scholastic tradition.\nAnswer: Thomas Stritch", "example_title": "Question Generation"}, {"text": "Classify the complexity of the following question based on the text as either deep or shallow.\nText: Many people who live in California are very concerned about the earth. They are worried that the earth is warming too much.\nQuestion: How can people in California and outside of California prevent warming?", "example_title": "Question Complexity"}, {"text": "Classify the complexity of the following question based on the text as either deep or shallow.\nText: Many people who live in California are very concerned about the earth. They are worried that the earth is warming too much.\nQuestion: What does it mean to warm the earth too much?", "example_title": "Question Category"}], "model-index": [{"name": "QAll-Flan-xl", "results": []}]}
transformers pytorch tf safetensors t5 text2text-generation generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #tf #safetensors #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 




# QAll-Flan-xl

This model is a fine-tuned version of google/flan-t5-xl on an unknown dataset.
It achieves the following results on the evaluation set:


## 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:
- optimizer: None
- training_precision: float32

### Training results



### Framework versions

- Transformers 4.25.1
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2

# QAll-Flan-xl

This model is a fine-tuned version of google/flan-t5-xl on an unknown dataset.
It achieves the following results on the evaluation set: ## 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:
- optimizer: None
- training_precision: float32 ### Training results ### Framework versions

- Transformers 4.25.1
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tf #safetensors #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
 # QAll-Flan-xl

This model is a fine-tuned version of google/flan-t5-xl on an unknown dataset.
It achieves the following results on the evaluation set: ## 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:
- optimizer: None
- training_precision: float32 ### Training results ### Framework versions

- Transformers 4.25.1
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #tf #safetensors #t5 #text2text-generation #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #text-generation-inference #region-us 
# QAll-Flan-xl

This model is a fine-tuned version of google/flan-t5-xl on an unknown dataset.
It achieves the following results on the evaluation set:## 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:
- optimizer: None
- training_precision: float32### Training results### Framework versions

- Transformers 4.25.1
- TensorFlow 2.11.0
- Datasets 2.10.1
- Tokenizers 0.13.2