---
license: apache-2.0
base_model: google/flan-t5-base
tags:
- generated_from_keras_callback
model-index:
- name: kaytoo2022/t5_technical_qa_with_react
  results: []
inference: true
library_name: transformers
pipeline_tag: text2text-generation
widget:
  - text: >-
      summarize: function Example() {
        let [isLoading, setIsLoading] = React.useState(false);
      
        let handlePress = () => {
          // Trigger button pending state
          setIsLoading(true);
      
          setTimeout(() => {
            // Cancel button pending state
            setIsLoading(false);
          }, 3000);
        };
      
        return (
          <Button variant="primary" isPending={isLoading} onPress={handlePress}>
            Click me!
          </Button>
        );
      }
    example_title: Question answering
  - text: >-
      question: What does the setTimeout function do? context: function Example() {
        let [isLoading, setIsLoading] = React.useState(false);
      
        let handlePress = () => {
          // Trigger button pending state
          setIsLoading(true);
      
          setTimeout(() => {
            // Cancel button pending state
            setIsLoading(false);
          }, 3000);
        };
      
        return (
          <Button variant="primary" isPending={isLoading} onPress={handlePress}>
            Click me!
          </Button>
        );
      }
    example_title: Summarization

---

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

# kaytoo2022/t5_technical_qa_with_react

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Train Loss: 2.0191
- Validation Loss: 2.0546
- Epoch: 3

## 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: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32

### Training results

| Train Loss | Validation Loss | Epoch |
|:----------:|:---------------:|:-----:|
| 2.5717     | 2.2548          | 0     |
| 2.2680     | 2.1607          | 1     |
| 2.1248     | 2.1008          | 2     |
| 2.0191     | 2.0546          | 3     |


### Framework versions

- Transformers 4.42.4
- TensorFlow 2.17.0
- Datasets 2.20.0
- Tokenizers 0.19.1