update readme

README.md

@@ -18,7 +18,7 @@ tags:
 
 datasets:
 
-- "projecte-aina/tecla"  
+- "projecte-aina/tecla"
 
 metrics:
 - accuracy
@@ -29,13 +29,12 @@ model-index:
   - task:
       type: text-classification
     dataset:
-      name: tecla
+      name: TeCla
       type: projecte-aina/tecla
     metrics:
       - name: Accuracy
         type: accuracy
         value: 0.740388810634613
-
 widget:
 
 - text: "Els Pets presenten el seu nou treball al Palau Sant Jordi." 
@@ -50,14 +49,60 @@ widget:
 
 ---
 
-# Catalan BERTa (RoBERTa-base) finetuned for Text Classification.
+# Catalan BERTa (roberta-base-ca) finetuned for Text Classification.
+
+## Table of Contents
+- [Model Description](#model-description)
+- [Intended Uses and Limitations](#intended-uses-and-limitations)
+- [How to Use](#how-to-use)
+- [Training](#training)
+  - [Training Data](#training-data)
+  - [Training Procedure](#training-procedure)
+- [Evaluation](#evaluation)
+   - [Variable and Metrics](#variable-and-metrics)
+   - [Evaluation Results](#evaluation-results)
+- [Licensing Information](#licensing-information)
+- [Citation Information](#citation-information)
+- [Funding](#funding)
+- [Contributions](#contributions)
+
+## Model description
+The **roberta-base-ca-cased-tc** is a Text Classification (TC) model for the Catalan language fine-tuned from the roberta-base-ca model, a [RoBERTa](https://arxiv.org/abs/1907.11692) base model pre-trained on a medium-size corpus collected from publicly available corpora and crawlers.
+
+## Intended Uses and Limitations
+
+**roberta-base-ca-cased-tc** model can be used to classify texts. The model is limited by its training dataset and may not generalize well for all use cases.
+
+## How to Use
+
+Here is how to use this model:
+
+```python
+from transformers import pipeline
+from pprint import pprint
+
+nlp = pipeline("text-classification", model="projecte-aina/roberta-base-ca-cased-tc")
+example = "Retards a quatre línies de Rodalies per una avaria entre Sants i plaça de Catalunya."
+
+tc_results = nlp(example)
+pprint(tc_results)
+```
 
-The **roberta-base-ca-cased-tc** is a Text Classification (TC) model for the Catalan language fine-tuned from the [BERTa](https://huggingface.co/PlanTL-GOB-ES/roberta-base-ca) model, a [RoBERTa](https://arxiv.org/abs/1907.11692) base model pre-trained on a medium-size corpus collected from publicly available corpora and crawlers (check the BERTa model card for more details).
+## Training
 
-## Datasets
-We used the TC dataset in Catalan called [TeCla](https://huggingface.co/datasets/projecte-aina/viquiquad) for training and evaluation.
+### Training data
+We used the TC dataset in Catalan called [TeCla](https://huggingface.co/datasets/projecte-aina/tecla) for training and evaluation.
 
-## Evaluation and results
+### Training Procedure
+The model was trained with a batch size of 16 and a learning rate of 5e-5 for 5 epochs. We then selected the best checkpoint using the downstream task metric in the corresponding development set and then evaluated it on the test set.
+
+## Evaluation
+
+### Variable and Metrics
+
+This model was finetuned maximizing accuracy.
+
+## Evaluation results
 We evaluated the _roberta-base-ca-cased-tc_ on the TeCla test set against standard multilingual and monolingual baselines:
 
 | Model        | TeCla (accuracy) | 
@@ -69,7 +114,11 @@ We evaluated the _roberta-base-ca-cased-tc_ on the TeCla test set against standa
 
 For more details, check the fine-tuning and evaluation scripts in the official [GitHub repository](https://github.com/projecte-aina/club).
 
-## Citing 
+## Licensing Information
+
+[Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)
+
+## Citation Information 
 If you use any of these resources (datasets or models) in your work, please cite our latest paper:
 ```bibtex
 @inproceedings{armengol-estape-etal-2021-multilingual,
@@ -91,4 +140,12 @@ If you use any of these resources (datasets or models) in your work, please cite
     doi = "10.18653/v1/2021.findings-acl.437",
     pages = "4933--4946",
 }
-```
+```
+
+### Funding
+This work was funded by the [Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).
+
+
+## Contributions
+
+[N/A]