Salesforce/wikisql
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How to use e22vvb/mt5_base_EN_sch_wiki with Transformers:
# Load model directly
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("e22vvb/mt5_base_EN_sch_wiki")
model = AutoModelForSeq2SeqLM.from_pretrained("e22vvb/mt5_base_EN_sch_wiki")This model is a fine-tuned version of google/mt5-base 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 | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
|---|---|---|---|---|---|---|
| 0.0 | 1.0 | 4627 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 2.0 | 9254 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 3.0 | 13881 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 4.0 | 18508 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 5.0 | 23135 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 6.0 | 27762 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 7.0 | 32389 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 8.0 | 37016 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 9.0 | 41643 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 10.0 | 46270 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 11.0 | 50897 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 12.0 | 55524 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 13.0 | 60151 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 14.0 | 64778 | nan | 0.0165 | 0.0087 | 0.0111 |
| 0.0 | 15.0 | 69405 | nan | 0.0165 | 0.0087 | 0.0111 |
Base model
google/mt5-base
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("e22vvb/mt5_base_EN_sch_wiki") model = AutoModelForSeq2SeqLM.from_pretrained("e22vvb/mt5_base_EN_sch_wiki")