Update README.md

README.md

@@ -1,11 +1,32 @@
 # robertuito-base-uncased
+# robertuito-base-deacc 
 
-**WORK IN PROGRESS**
+# RoBERTuito
+## A pre-trained language model for social media text in Spanish
 
-RoBERTa model trained on tweets. 
+[**READ THE FULL PAPER**](https://arxiv.org/abs/2111.09453)
+[Github Repository](https://github.com/pysentimiento/robertuito)
 
-For the time being, please use [this function](https://github.com/finiteautomata/finetune_vs_scratch/blob/main/finetune_vs_scratch/preprocessing.py#L13) before feeding it to the model. We still need to create a proper tokenizer for this model
+*RoBERTuito* is a pre-trained language model for user-generated content in Spanish, trained following RoBERTa guidelines on 500 million tweets. *RoBERTuito* comes in 3 flavors: cased, uncased, and uncased+deaccented.
 
+We tested *RoBERTuito* on a benchmark of tasks involving user-generated text in Spanish. It outperforms other pre-trained language models for this language such as *BETO*, *BERTin* and *RoBERTa-BNE*. The 4 tasks selected for evaluation were: Hate Speech Detection (using SemEval 2019 Task 5, HatEval dataset), Sentiment and Emotion Analysis (using TASS 2020 datasets), and Irony detection (using IrosVa 2019 dataset).
+
+| model              | hate speech     | sentiment analysis   | emotion analysis   | irony detection  |   score |
+|:-------------------|:----------------|:---------------------|:-------------------|:-----------------|---------:|
+| robertuito-uncased | 0.801 ± 0.010  | 0.707 ± 0.004       | 0.551 ± 0.011     | 0.736 ± 0.008   | 0.6987  |
+| robertuito-deacc   | 0.798 ± 0.008  | 0.702 ± 0.004       | 0.543 ± 0.015     | 0.740 ± 0.006   | 0.6958  |
+| robertuito-cased   | 0.790 ± 0.012  | 0.701 ± 0.012       | 0.519 ± 0.032     | 0.719 ± 0.023   | 0.6822  |
+| roberta-bne        | 0.766 ± 0.015  | 0.669 ± 0.006       | 0.533 ± 0.011     | 0.723 ± 0.017   | 0.6726  |
+| bertin             | 0.767 ± 0.005  | 0.665 ± 0.003       | 0.518 ± 0.012     | 0.716 ± 0.008   | 0.6666  |
+| beto-cased         | 0.768 ± 0.012  | 0.665 ± 0.004       | 0.521 ± 0.012     | 0.706 ± 0.007   | 0.6651  |
+| beto-uncased       | 0.757 ± 0.012  | 0.649 ± 0.005       | 0.521 ± 0.006     | 0.702 ± 0.008   | 0.6571  |
+
+
+We release the pre-trained models on huggingface model hub:
+
+- [RoBERTuito uncased](https://huggingface.co/pysentimiento/robertuito-base-uncased)
+- [RoBERTuito cased](https://huggingface.co/pysentimiento/robertuito-base-cased)
+- [RoBERTuito deacc](https://huggingface.co/pysentimiento/robertuito-base-deacc)
 
 
 ## Masked LM
@@ -17,3 +38,73 @@ Este es un día<mask>
 ```
 
 don't put a space between `día` and `<mask>`
+
+
+## Usage
+
+**IMPORTANT -- READ THIS FIRST**
+
+*RoBERTuito* is not yet fully-integrated into `huggingface/transformers`. To use it, first install `pysentimiento`
+
+```bash
+pip install pysentimiento
+```
+
+and preprocess text using `pysentimiento.preprocessing.preprocess_tweet` before feeding it into the tokenizer
+
+```python
+from transformers import AutoTokenizer
+from pysentimiento.preprocessing import preprocess_tweet
+
+tokenizer = AutoTokenizer.from_pretrained('pysentimiento/robertuito-base-cased')
+
+text = "Esto es un tweet estoy usando #Robertuito @pysentimiento 🤣"
+preprocessed_text = preprocess_tweet(text, ha)
+
+tokenizer.tokenize(preprocessed_text)
+# ['<s>','▁Esto','▁es','▁un','▁tweet','▁estoy','▁usando','▁','▁hashtag','▁','▁ro','bert','uito','▁@usuario','▁','▁emoji','▁cara','▁revolviéndose','▁de','▁la','▁risa','▁emoji','</s>']
+```
+
+We are working on integrating this preprocessing step into a Tokenizer within `transformers` library
+
+## Development
+
+### Installing
+
+We use `python==3.7` and `poetry` to manage dependencies.
+
+```bash
+pip install poetry
+poetry install
+```
+
+### Benchmarking
+
+To run benchmarks
+
+```bash
+python bin/run_benchmark.py <model_name> --times 5 --output_path <output_path>
+```
+
+Check [RUN_BENCHMARKS](RUN_BENCHMARKS.md) for all experiments
+
+### Smoke test
+Test the benchmark running
+
+```
+./smoke_test.sh
+```
+## Citation
+
+If you use *RoBERTuito*, please cite our paper:
+
+```bibtex
+@misc{perez2021robertuito,
+      title={RoBERTuito: a pre-trained language model for social media text in Spanish},
+      author={Juan Manuel Pérez and Damián A. Furman and Laura Alonso Alemany and Franco Luque},
+      year={2021},
+      eprint={2111.09453},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+}
+```