Remove MD emojis (#4602)
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@@ -3,11 +3,11 @@ language: italian
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thumbnail:
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---
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# Italian BERT :it: fine-tuned on SQuAD_it v1 :book: :mag: :question:
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# Italian BERT fine-tuned on SQuAD_it v1
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[Italian BERT base cased](https://huggingface.co/dbmdz/bert-base-italian-cased) fine-tuned on [italian SQuAD](https://github.com/crux82/squad-it) for **Q&A** downstream task.
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## Details of Italian BERT :hugs: :it:
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## Details of Italian BERT
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The source data for the Italian BERT model consists of a recent Wikipedia dump and various texts from the OPUS corpora collection. The final training corpus has a size of 13GB and 2,050,057,573 tokens.
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@@ -18,7 +18,7 @@ More in its official [model card](https://huggingface.co/dbmdz/bert-base-italian
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Created by [Stefan](https://huggingface.co/stefan-it) at [MDZ](https://huggingface.co/dbmdz)
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## Details of the downstream task (Q&A) - Dataset :books:
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## Details of the downstream task (Q&A) - Dataset 📚 🧐 ❓
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[Italian SQuAD v1.1](https://rajpurkar.github.io/SQuAD-explorer/) is derived from the SQuAD dataset and it is obtained through semi-automatic translation of the SQuAD dataset
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into Italian. It represents a large-scale dataset for open question answering processes on factoid questions in Italian.
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@@ -29,12 +29,12 @@ into Italian. It represents a large-scale dataset for open question answering pr
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More details about SQuAD-it can be found in [Croce et al. 2018]. The original paper can be found at this [link](https://link.springer.com/chapter/10.1007/978-3-030-03840-3_29).
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## Model training :gear:
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## Model training 🏋️
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The model was trained on a Tesla P100 GPU and 25GB of RAM.
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The script for fine tuning can be found [here](https://github.com/huggingface/transformers/blob/master/examples/question-answering/run_squad.py)
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## Results :chart_with_upwards_trend:
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## Results 📝
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| Metric | # Value |
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| ------ | --------- |
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@@ -58,14 +58,14 @@ The script for fine tuning can be found [here](https://github.com/huggingface/tr
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}
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```
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## Comparison :balance_scale:
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## Comparison ⚖️
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| Model | EM | F1 score |
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| -------------------------------------------------------------------------------------------------------------------------------- | --------- | --------- |
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| [DrQA-it trained on SQuAD-it ](https://github.com/crux82/squad-it/blob/master/README.md#evaluating-a-neural-model-over-squad-it) | 56.1 | 65.9 |
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| This one | **62.51** | **74.16** |
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## Model in action :rocket:
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## Model in action 🚀
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Fast usage with **pipelines** 🧪
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