Salesforce/wikisql
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How to use FadwaTalks/t5-small-finetuned-wikisql with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("FadwaTalks/t5-small-finetuned-wikisql")
model = AutoModelForSeq2SeqLM.from_pretrained("FadwaTalks/t5-small-finetuned-wikisql", device_map="auto")This model is a fine-tuned version of t5-small on the wikisql 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 | Model Preparation Time | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|---|
| 0.1942 | 1.0 | 4049 | 0.1561 | 0.008 | 0.8709 | 0.7597 | 0.8545 | 0.8546 |
| 0.1646 | 2.0 | 8098 | 0.1373 | 0.008 | 0.8771 | 0.7745 | 0.8624 | 0.8625 |
| 0.147 | 3.0 | 12147 | 0.1297 | 0.008 | 0.8794 | 0.7796 | 0.8654 | 0.8655 |
| 0.1412 | 4.0 | 16196 | 0.1256 | 0.008 | 0.8795 | 0.782 | 0.866 | 0.8661 |
| 0.14 | 5.0 | 20245 | 0.1247 | 0.008 | 0.8801 | 0.7827 | 0.8666 | 0.8667 |
Base model
google-t5/t5-small