wiselinjayajos/squad_modified_for_t5_qg
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How to use BOULLOUL/End2EndQGT5 with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("BOULLOUL/End2EndQGT5")
model = AutoModelForSeq2SeqLM.from_pretrained("BOULLOUL/End2EndQGT5")This model is a fine-tuned version of t5-base on the squad v1.1 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 |
|---|---|---|---|
| 2.5879 | 0.34 | 100 | 1.9133 |
| 1.9688 | 0.68 | 200 | 1.7313 |
| 1.8513 | 1.02 | 300 | 1.6691 |
| 1.7459 | 1.36 | 400 | 1.6413 |
| 1.7206 | 1.69 | 500 | 1.6200 |
| 1.7026 | 2.03 | 600 | 1.6101 |
| 1.6447 | 2.37 | 700 | 1.5983 |
| 1.6402 | 2.71 | 800 | 1.5979 |
| 1.6332 | 3.05 | 900 | 1.5924 |
| 1.5953 | 3.39 | 1000 | 1.5877 |
| 1.5922 | 3.73 | 1100 | 1.5854 |
| 1.5832 | 4.07 | 1200 | 1.5830 |
| 1.5726 | 4.41 | 1300 | 1.5799 |
| 1.5587 | 4.75 | 1400 | 1.5789 |