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congretimbau – AI Model by belisards | AlphaNeural AI
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belisards
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congretimbau
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transformers
tensorboard
safetensors
bert
fill-mask
generated_from_trainer
pt
belisards/ementas_senado_1946_2024
belisards/ementas_camarabr_1934_2024
neuralmind/bert-base-portuguese-cased
finetune
mit
autotrain_compatible
endpoints_compatible
us
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congretimbau
This model is a continuously trained version of
BERTimbau
on a dataset with bills of Brazilian law proposals.
It achieves the following results on the evaluation set:
eval_loss: 0.4885
eval_runtime: 798.5704
eval_samples_per_second: 169.279
eval_steps_per_second: 1.324
epoch: 2.3669
step: 10000
Training and evaluation data
Data from the Chamber of Deputies and the Federal Senate.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
learning_rate: 3e-05
train_batch_size: 128
eval_batch_size: 128
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 300
num_epochs: 10
Framework versions
Transformers 4.45.1
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.20.0