
# BR_BERTo

Portuguese (Brazil) model for text inference.

## Params

Trained on a corpus of 6_993_330 sentences.

- Vocab size: 150_000
- RobertaForMaskedLM  size : 512
- Num train epochs: 3
- Time to train: ~10days (on GCP with a Nvidia T4)

I follow the great tutorial from HuggingFace team:

[How to train a new language model from scratch using Transformers and Tokenizers](https://huggingface.co/blog/how-to-train)

More infor here:

[BR_BERTo](https://github.com/rdenadai/BR-BERTo)

{"language": "pt", "tags": ["portuguese", "brazil", "pt_BR"], "widget": [{"text": "gostei muito dessa <mask>"}]}
transformers pytorch jax safetensors roberta fill-mask portuguese brazil pt_BR pt autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #jax #safetensors #roberta #fill-mask #portuguese #brazil #pt_BR #pt #autotrain_compatible #endpoints_compatible #region-us 


# BR_BERTo

Portuguese (Brazil) model for text inference.

## Params

Trained on a corpus of 6_993_330 sentences.

- Vocab size: 150_000
- RobertaForMaskedLM  size : 512
- Num train epochs: 3
- Time to train: ~10days (on GCP with a Nvidia T4)

I follow the great tutorial from HuggingFace team:

How to train a new language model from scratch using Transformers and Tokenizers

More infor here:

BR_BERTo

# BR_BERTo

Portuguese (Brazil) model for text inference. ## Params

Trained on a corpus of 6_993_330 sentences.

- Vocab size: 150_000
- RobertaForMaskedLM  size : 512
- Num train epochs: 3
- Time to train: ~10days (on GCP with a Nvidia T4)

I follow the great tutorial from HuggingFace team:

How to train a new language model from scratch using Transformers and Tokenizers

More infor here:

BR_BERTo
TAGS
#transformers #pytorch #jax #safetensors #roberta #fill-mask #portuguese #brazil #pt_BR #pt #autotrain_compatible #endpoints_compatible #region-us 
 # BR_BERTo

Portuguese (Brazil) model for text inference. ## Params

Trained on a corpus of 6_993_330 sentences.

- Vocab size: 150_000
- RobertaForMaskedLM  size : 512
- Num train epochs: 3
- Time to train: ~10days (on GCP with a Nvidia T4)

I follow the great tutorial from HuggingFace team:

How to train a new language model from scratch using Transformers and Tokenizers

More infor here:

BR_BERTo
passage: TAGS
#transformers #pytorch #jax #safetensors #roberta #fill-mask #portuguese #brazil #pt_BR #pt #autotrain_compatible #endpoints_compatible #region-us 
# BR_BERTo

Portuguese (Brazil) model for text inference.## Params

Trained on a corpus of 6_993_330 sentences.

- Vocab size: 150_000
- RobertaForMaskedLM  size : 512
- Num train epochs: 3
- Time to train: ~10days (on GCP with a Nvidia T4)

I follow the great tutorial from HuggingFace team:

How to train a new language model from scratch using Transformers and Tokenizers

More infor here:

BR_BERTo