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Unverified Commit bac1cc4d authored by Manuel Romero's avatar Manuel Romero Committed by GitHub
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Remove MD emojis (#4602)

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# Italian BERT :it: fine-tuned on SQuAD_it v1 :book: :mag: :question: # Italian BERT fine-tuned on SQuAD_it v1
[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. [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.
## Details of Italian BERT :hugs: :it: ## Details of Italian BERT
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. 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.
...@@ -18,7 +18,7 @@ More in its official [model card](https://huggingface.co/dbmdz/bert-base-italian ...@@ -18,7 +18,7 @@ More in its official [model card](https://huggingface.co/dbmdz/bert-base-italian
Created by [Stefan](https://huggingface.co/stefan-it) at [MDZ](https://huggingface.co/dbmdz) Created by [Stefan](https://huggingface.co/stefan-it) at [MDZ](https://huggingface.co/dbmdz)
## Details of the downstream task (Q&A) - Dataset :books: ## Details of the downstream task (Q&A) - Dataset 📚 🧐 ❓
[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 [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
into Italian. It represents a large-scale dataset for open question answering processes on factoid questions in Italian. into Italian. It represents a large-scale dataset for open question answering processes on factoid questions in Italian.
...@@ -29,12 +29,12 @@ into Italian. It represents a large-scale dataset for open question answering pr ...@@ -29,12 +29,12 @@ into Italian. It represents a large-scale dataset for open question answering pr
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). 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).
## Model training :gear: ## Model training 🏋️‍
The model was trained on a Tesla P100 GPU and 25GB of RAM. The model was trained on a Tesla P100 GPU and 25GB of RAM.
The script for fine tuning can be found [here](https://github.com/huggingface/transformers/blob/master/examples/question-answering/run_squad.py) The script for fine tuning can be found [here](https://github.com/huggingface/transformers/blob/master/examples/question-answering/run_squad.py)
## Results :chart_with_upwards_trend: ## Results 📝
| Metric | # Value | | Metric | # Value |
| ------ | --------- | | ------ | --------- |
...@@ -58,14 +58,14 @@ The script for fine tuning can be found [here](https://github.com/huggingface/tr ...@@ -58,14 +58,14 @@ The script for fine tuning can be found [here](https://github.com/huggingface/tr
} }
``` ```
## Comparison :balance_scale: ## Comparison ⚖️
| Model | EM | F1 score | | Model | EM | F1 score |
| -------------------------------------------------------------------------------------------------------------------------------- | --------- | --------- | | -------------------------------------------------------------------------------------------------------------------------------- | --------- | --------- |
| [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 | | [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 |
| This one | **62.51** | **74.16** | | This one | **62.51** | **74.16** |
## Model in action :rocket: ## Model in action 🚀
Fast usage with **pipelines** 🧪 Fast usage with **pipelines** 🧪
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