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@@ -91,6 +91,7 @@ By removing the decoder we can *half the original number of parameters* (thus ha
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  0. [Usage](##usage)
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  1. [Why use T5ForSequenceClassification?](##why-use-t5forsequenceclassification?)
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  2. [T5ForClassification vs T5](##t5forclassification-vs-t5)
 
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  ## Usage
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  **T5ForSequenceClassification** supports the task of zero-shot classification.
@@ -124,5 +125,13 @@ Benefits and Drawbacks:
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  - (**+**) No generation mistakes and faster prediction (no generation latency)
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  - (**-**) Looses text-to-text ability
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  Special thanks to [philschmid](https://huggingface.co/philschmid) for making a Flan-T5-xxl [checkpoint](https://huggingface.co/philschmid/flan-t5-xxl-sharded-fp16) in fp16.
 
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  0. [Usage](##usage)
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  1. [Why use T5ForSequenceClassification?](##why-use-t5forsequenceclassification?)
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  2. [T5ForClassification vs T5](##t5forclassification-vs-t5)
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+ 3. [Results](##results)
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  ## Usage
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  **T5ForSequenceClassification** supports the task of zero-shot classification.
 
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  - (**+**) No generation mistakes and faster prediction (no generation latency)
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  - (**-**) Looses text-to-text ability
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+ ## Results
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+ Results on the validation data of training tasks:
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+ | Dataset | Accuracy | F1 |
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+ |:-------:|:--------:|:--:|
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+ | MNLI (m)| 1 | 0.905 |
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+ | MNLI (mm) | 0.900 |0.900 |
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+ | SNLI | 0.900 |0.900 |
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+ | SciTail | 0.900 |0.900 |
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  Special thanks to [philschmid](https://huggingface.co/philschmid) for making a Flan-T5-xxl [checkpoint](https://huggingface.co/philschmid/flan-t5-xxl-sharded-fp16) in fp16.