File size: 2,764 Bytes
4f63f07 e4e1d64 b09d49c 170d8f0 4f63f07 e3da494 4f63f07 a3dbb44 a5b1104 e3da494 4f63f07 b09d49c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 | ---
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 |