---
license: afl-3.0
language:
- hu
---

# Model Card for Model ID

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This model is an extract of a mT5 that only supports English and Hungarian.

## Model Details

### Model Description

This is a smaller version of the google/mt5-base model with only Hungarian and some English embeddings left.

The original model has 582M parameters, with 384M of them being input and output embeddings.
After shrinking the sentencepiece vocabulary from 250K to 30K (top 10K English and top 20K Hungarian tokens) 
the number of model parameters reduced to 244M parameters, and model size reduced from 2.2GB to 0.9GB - 42% of the original one.


This model is based on the description of [cointegrated/rut5-base](https://huggingface.co/cointegrated/rut5-base). 
The creation of this model is described in the post [How to adapt a multilingual T5 model for a single language](https://towardsdatascience.com/how-to-adapt-a-multilingual-t5-model-for-a-single-language-b9f94f3d9c90) along with the source code.

- **Developed by:** [Gábor Madarász]
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- **Model type:** [More Information Needed]
- **Language(s) (NLP):** [Hungarian, English]
- **License:** [More Information Needed]
- **Finetuned from model [optional]:** The model did not finetuned for any downstream tasks

### Model Sources [optional]

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## Uses

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### Direct Use

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### Out-of-Scope Use

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## Bias, Risks, and Limitations

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### Recommendations

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Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.

## How to Get Started with the Model

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## Training Details

### Training Data

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### Training Procedure 

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#### Preprocessing [optional]

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#### Training Hyperparameters

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#### Speeds, Sizes, Times [optional]

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## Evaluation

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### Testing Data, Factors & Metrics

#### Testing Data

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#### Factors

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#### Metrics

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### Results

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#### Summary



## Model Examination [optional]

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## Environmental Impact

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Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).

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## Technical Specifications [optional]

### Model Architecture and Objective

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## Citation [optional]

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## Glossary [optional]

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