tiagoblima/preprocessed-du-qg-squadv1_pt
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How to use tiagoblima/t5_base-qg-aas-oficial with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("tiagoblima/t5_base-qg-aas-oficial")
model = AutoModelForSeq2SeqLM.from_pretrained("tiagoblima/t5_base-qg-aas-oficial", device_map="auto")This model is a fine-tuned version of unicamp-dl/ptt5-base-portuguese-vocab on the tiagoblima/preprocessed-du-qg-squadv1_pt 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 |
|---|---|---|---|
| 2.1854 | 1.0 | 1386 | 2.0911 |
| 2.048 | 2.0 | 2772 | 2.0533 |
| 1.9295 | 3.0 | 4158 | 2.0422 |
| 1.9142 | 4.0 | 5544 | 2.0362 |
| 1.8512 | 5.0 | 6930 | 2.0399 |
Base model
unicamp-dl/ptt5-base-portuguese-vocab