Update README.md

README.md

@@ -34,4 +34,168 @@ metrics:
 - recall
 language:
 - it
----
+---
+# Model Card for raicrits/newsClassifier_v1
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+This model analyses the input text and provides the class the text belongs to among the follofing ones:
+0"sport"
+1"giustizia-criminalita-sicurezza"
+2"editoria-stampa-mass_media"
+3"lavoro-previdenza"
+4"trasporti"
+5"cultura-scienze_umane"
+6"esteri"
+7"istruzione-formazione"
+8"industria-impresa-produzione"
+9"vita_e_cultura_religiosa"
+10"sanita-salute"
+11"economia-credito-finanza"
+12"musica_e_spettacolo"
+13"cronaca"
+14"ambiente-natura-territorio"
+15"politica-partiti-istituzioni-sindacati"
+16"avvenimenti-celebrazioni-eventi_storici"
+17"consumi-servizi"
+18"individuo-famiglia-associazioni-societa"
+19"commercio"
+20"scienze-tecnologie"
+21"pubblica_amministrazione-enti_locali"
+22"tempo_libero"
+23"arte-artigianato"
+24"usi_e_costumi"
+25"beni_culturali"
+26"agricoltura-zootecnia"
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** Alberto Messina ([email protected])
+- **Model type:** BERT for Sequence Classification
+- **Language(s) (NLP):** Italian
+- **License:** TBD
+- **Finetuned from model:** https://huggingface.co/xlm-roberta-base
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** N/A
+- **Paper [optional]:** N/A
+- **Demo [optional]:** N/A
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+The model should be used giving a short paragraph of text in Italian as input 
+about which it is requested to get the most probable class.
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+TBA
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+The model should not be used as a general purpose classifier, i.e. on text which is not originated from news programme transcription or siilar content.
+
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+The training dataset is made up of automatic transcriptions from RAI Italian newscasts, therefore there is an intrinsic bias in the kind
+of topics included in the dataset.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+TBA
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+TBA
+
+### Training Procedure 
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+TBA
+
+
+#### Training Hyperparameters
+
+- **Training regime:** Mixed Precision 
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+TBA
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Data Card if possible. -->
+
+TBA
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+TBA
+
+### Results
+
+TBA
+
+#### Summary
+
+TBA
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** 2 NVIDIA A100/40Gb
+- **Hours used:** 2
+- **Cloud Provider:** Private Infrastructure
+- **Carbon Emitted:** 0.22 kg CO2 eq.
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+TBA
+
+## More Information [optional]
+
+TBA
+
+## Model Card Authors [optional]
+
+Alberto Messina
+
+## Model Card Contact
+
+[email protected]
+