Model Card for raicrits/newsClassifier_v1
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
- 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]
- Repository: N/A
- Paper [optional]: N/A
- Demo [optional]: N/A
Uses
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
TBA
Out-of-Scope Use
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
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
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Training Procedure
Preprocessing [optional]
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Training Hyperparameters
- Training regime: Mixed Precision
Evaluation
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Testing Data, Factors & Metrics
Testing Data
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Metrics
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Results
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Summary
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
- Hardware Type: 2 NVIDIA A100/40Gb
- Hours used: 2
- Cloud Provider: Private Infrastructure
- Carbon Emitted: 0.22 kg CO2 eq.
Glossary [optional]
TBA
More Information [optional]
TBA
Model Card Authors [optional]
Alberto Messina
Model Card Contact
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