Luciano/lener_br_text_to_lm
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How to use Luciano/bertimbau-base-finetuned-lener-br with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("fill-mask", model="Luciano/bertimbau-base-finetuned-lener-br") # Load model directly
from transformers import AutoTokenizer, AutoModelForMaskedLM
tokenizer = AutoTokenizer.from_pretrained("Luciano/bertimbau-base-finetuned-lener-br")
model = AutoModelForMaskedLM.from_pretrained("Luciano/bertimbau-base-finetuned-lener-br")This model is a fine-tuned version of neuralmind/bert-base-portuguese-cased on the Luciano/lener_br_text_to_lm dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3167 | 1.0 | 2079 | 1.1163 |
| 1.1683 | 2.0 | 4158 | 1.0594 |
| 1.0648 | 3.0 | 6237 | 1.0501 |
| 1.0228 | 4.0 | 8316 | 0.9693 |
| 0.9662 | 5.0 | 10395 | 0.9847 |
| 0.9422 | 6.0 | 12474 | 0.9556 |
| 0.8696 | 7.0 | 14553 | 0.8978 |
| 0.7856 | 8.0 | 16632 | nan |
| 0.7849 | 9.0 | 18711 | 0.9192 |
| 0.7559 | 10.0 | 20790 | 0.8536 |
| 0.7564 | 11.0 | 22869 | 0.9230 |
| 0.7641 | 12.0 | 24948 | 0.8852 |
| 0.7007 | 13.0 | 27027 | 0.8616 |
| 0.7139 | 14.0 | 29106 | 0.8419 |
| 0.6543 | 15.0 | 31185 | 0.8460 |