mascIT/bertina-3M

bertina-3M is an italian foundational model based on bert, pretrained from scratch on 30GB of italian Wikipedia articles (10M sentences, 329M tokens).

It has 3M parameters and uses a 512 context window size.

The project is still a work in progress, new versions will come with time.

Use it as a foundational model to be finetuned on specific italian tasks.

Training

• epochs: 4

• lr: 4e-4

• optim: AdamW (beta_1=0.8)

• weight_decay: 1e-2

• Dev set perplexity: 19 (it's a 12MB model!)

Evaluation (UINAUIL)

Following the UINAUIL setup we can summarise the following results on BERTINA-3M:

CLASSIFICATION TASKS

task,type,p,r,f1,acc
haspeede,classification,0.699,0.687,0.680,0.685
ironita,classification,0.701,0.701,0.701,0.701
sentipolc,classification,0.649,0.588,0.587,0.560

ENTAILMENT TASKS

task,type,p,r,f1,acc
textualentailment,entailment,0.423,0.530,0.401,0.530

SEQUENCE TASKS

task,type,acc
eventi,NER,0.835
facta,NER,0.967

License

BERTINA-3M can be freely used for research and commercial purposes.

Citation

If you're using BERTINA-3M in your scientific work, please cite with:

@misc{
  Sciancalepore,
  title={mascit/bertina-3M},
  url={https://huggingface.co/mascIT/bertina-3M},
  journal={mascIT/bertina-3M · Hugging Face},
  publisher={mascIT},
  author={Sciancalepore, Mauro}
}