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README.md
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---
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language:
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- ar
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datasets:
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- mc4
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- oscar
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- arabic_billion_words
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---
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# arabic-t5-small
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This is a T5v1.1 (small) trained on the concatenation of the Arabic Billion Words corpus and the Arabic subsets of the mC4 and Oscar datasets. The model could only be trained for about `10%` of the whole dataset due to time limitations.
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## Training parameters
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| :-------------------: | :-----------: |
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| steps | `22'000` |
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| Training batch size | `384` |
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| Evaluation batch size | `768` |
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| learning rate | `1e-2` |
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| dtype | `jnp.float32` |
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## Note for finetuning:
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This model was pretrained with dropout turned off, so the default `dropout_rate` in the model config is `0`.
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To finetune the model dropout should be turned be back on, like this:
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```python
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model = T5ForConditionalGeneration.from_pretrained("flax-community/arabic-t5-small", dropout_rate=0.1)
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```
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or,
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```python
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model = AutoModelForSeq2SeqLM.from_pretrained("flax-community/arabic-t5-small", dropout_rate=0.1)
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```
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