tiagoblima/preprocessed-du-qg-squadv1_pt
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How to use tiagoblima/t5_base-qg-aap-oficial with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("tiagoblima/t5_base-qg-aap-oficial")
model = AutoModelForSeq2SeqLM.from_pretrained("tiagoblima/t5_base-qg-aap-oficial")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 |
|---|---|---|---|
| 1.9061 | 1.0 | 1386 | 1.6450 |
| 1.7685 | 2.0 | 2772 | 1.5084 |
| 1.6527 | 3.0 | 4158 | 1.4205 |
| 1.6295 | 4.0 | 5544 | 1.3706 |
| 1.5809 | 5.0 | 6930 | 1.3527 |
Base model
unicamp-dl/ptt5-base-portuguese-vocab