Hugging Face's logo

mousaazari
/
t5-text2sql

Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Model card Files
xet
 Metrics Community
5
mousaazari commited on
Commit
144f6ac
·
1 Parent(s): 682926f

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +34 -34
README.md CHANGED
@@ -14,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
14
 
15
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
16
  It achieves the following results on the evaluation set:
17
- - Loss: 0.0605
18
- - Rouge2 Precision: 0.7259
19
- - Rouge2 Recall: 0.1626
20
- - Rouge2 Fmeasure: 0.2617
21
 
22
  ## Model description
23
 
@@ -48,36 +48,36 @@ The following hyperparameters were used during training:
48
 
49
  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
50
  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
51
- | No log | 1.0 | 50 | 0.3418 | 0.5312 | 0.1269 | 0.2015 |
52
- | No log | 2.0 | 100 | 0.1792 | 0.5827 | 0.1484 | 0.2329 |
53
- | No log | 3.0 | 150 | 0.1360 | 0.6261 | 0.145 | 0.2323 |
54
- | No log | 4.0 | 200 | 0.1125 | 0.6427 | 0.1444 | 0.2332 |
55
- | No log | 5.0 | 250 | 0.0990 | 0.6455 | 0.1459 | 0.2338 |
56
- | No log | 6.0 | 300 | 0.0897 | 0.6538 | 0.1476 | 0.237 |
57
- | No log | 7.0 | 350 | 0.0836 | 0.6444 | 0.1471 | 0.2363 |
58
- | No log | 8.0 | 400 | 0.0790 | 0.6818 | 0.1541 | 0.2477 |
59
- | No log | 9.0 | 450 | 0.0756 | 0.6966 | 0.1565 | 0.2518 |
60
- | 0.2853 | 10.0 | 500 | 0.0728 | 0.6819 | 0.1534 | 0.2468 |
61
- | 0.2853 | 11.0 | 550 | 0.0710 | 0.7059 | 0.1595 | 0.2566 |
62
- | 0.2853 | 12.0 | 600 | 0.0700 | 0.6955 | 0.1569 | 0.2523 |
63
- | 0.2853 | 13.0 | 650 | 0.0695 | 0.7015 | 0.1568 | 0.2525 |
64
- | 0.2853 | 14.0 | 700 | 0.0668 | 0.7017 | 0.157 | 0.2531 |
65
- | 0.2853 | 15.0 | 750 | 0.0650 | 0.6924 | 0.1554 | 0.2504 |
66
- | 0.2853 | 16.0 | 800 | 0.0652 | 0.6942 | 0.1551 | 0.2499 |
67
- | 0.2853 | 17.0 | 850 | 0.0636 | 0.6877 | 0.1528 | 0.2463 |
68
- | 0.2853 | 18.0 | 900 | 0.0625 | 0.7023 | 0.1567 | 0.2526 |
69
- | 0.2853 | 19.0 | 950 | 0.0638 | 0.7092 | 0.1591 | 0.2558 |
70
- | 0.0584 | 20.0 | 1000 | 0.0624 | 0.7043 | 0.158 | 0.2545 |
71
- | 0.0584 | 21.0 | 1050 | 0.0636 | 0.7032 | 0.1573 | 0.2534 |
72
- | 0.0584 | 22.0 | 1100 | 0.0612 | 0.6996 | 0.1558 | 0.2511 |
73
- | 0.0584 | 23.0 | 1150 | 0.0627 | 0.7184 | 0.1619 | 0.2607 |
74
- | 0.0584 | 24.0 | 1200 | 0.0615 | 0.7165 | 0.1607 | 0.2587 |
75
- | 0.0584 | 25.0 | 1250 | 0.0610 | 0.715 | 0.1601 | 0.2578 |
76
- | 0.0584 | 26.0 | 1300 | 0.0606 | 0.7218 | 0.1626 | 0.2616 |
77
- | 0.0584 | 27.0 | 1350 | 0.0602 | 0.7269 | 0.1634 | 0.2628 |
78
- | 0.0584 | 28.0 | 1400 | 0.0605 | 0.7203 | 0.1618 | 0.2605 |
79
- | 0.0584 | 29.0 | 1450 | 0.0604 | 0.7259 | 0.1626 | 0.2617 |
80
- | 0.0442 | 30.0 | 1500 | 0.0605 | 0.7259 | 0.1626 | 0.2617 |
81
 
82
 
83
  ### Framework versions
 
14
 
15
  This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
16
  It achieves the following results on the evaluation set:
17
+ - Loss: 0.0621
18
+ - Rouge2 Precision: 0.7239
19
+ - Rouge2 Recall: 0.1683
20
+ - Rouge2 Fmeasure: 0.2685
21
 
22
  ## Model description
23
 
 
48
 
49
  | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
50
  |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
51
+ | No log | 1.0 | 50 | 0.4350 | 0.3583 | 0.0648 | 0.1084 |
52
+ | No log | 2.0 | 100 | 0.2193 | 0.572 | 0.1265 | 0.2046 |
53
+ | No log | 3.0 | 150 | 0.1605 | 0.5637 | 0.1352 | 0.2151 |
54
+ | No log | 4.0 | 200 | 0.1274 | 0.6209 | 0.1501 | 0.2385 |
55
+ | No log | 5.0 | 250 | 0.1132 | 0.6115 | 0.1456 | 0.2319 |
56
+ | No log | 6.0 | 300 | 0.1004 | 0.6029 | 0.144 | 0.2283 |
57
+ | No log | 7.0 | 350 | 0.0943 | 0.611 | 0.1485 | 0.2348 |
58
+ | No log | 8.0 | 400 | 0.0868 | 0.6605 | 0.1557 | 0.2473 |
59
+ | No log | 9.0 | 450 | 0.0820 | 0.6587 | 0.1544 | 0.246 |
60
+ | 0.3249 | 10.0 | 500 | 0.0792 | 0.6429 | 0.1523 | 0.2421 |
61
+ | 0.3249 | 11.0 | 550 | 0.0750 | 0.6516 | 0.1538 | 0.2444 |
62
+ | 0.3249 | 12.0 | 600 | 0.0742 | 0.6679 | 0.1575 | 0.2512 |
63
+ | 0.3249 | 13.0 | 650 | 0.0722 | 0.6778 | 0.1583 | 0.2524 |
64
+ | 0.3249 | 14.0 | 700 | 0.0695 | 0.6939 | 0.161 | 0.2571 |
65
+ | 0.3249 | 15.0 | 750 | 0.0683 | 0.6813 | 0.1553 | 0.2486 |
66
+ | 0.3249 | 16.0 | 800 | 0.0680 | 0.6833 | 0.1568 | 0.2506 |
67
+ | 0.3249 | 17.0 | 850 | 0.0668 | 0.6869 | 0.1577 | 0.252 |
68
+ | 0.3249 | 18.0 | 900 | 0.0660 | 0.7064 | 0.1627 | 0.2597 |
69
+ | 0.3249 | 19.0 | 950 | 0.0660 | 0.7405 | 0.1726 | 0.2752 |
70
+ | 0.0684 | 20.0 | 1000 | 0.0653 | 0.7295 | 0.171 | 0.2722 |
71
+ | 0.0684 | 21.0 | 1050 | 0.0646 | 0.7337 | 0.1709 | 0.2728 |
72
+ | 0.0684 | 22.0 | 1100 | 0.0632 | 0.7196 | 0.1678 | 0.2673 |
73
+ | 0.0684 | 23.0 | 1150 | 0.0633 | 0.7098 | 0.1651 | 0.2635 |
74
+ | 0.0684 | 24.0 | 1200 | 0.0622 | 0.7214 | 0.1682 | 0.2681 |
75
+ | 0.0684 | 25.0 | 1250 | 0.0626 | 0.7274 | 0.1692 | 0.2699 |
76
+ | 0.0684 | 26.0 | 1300 | 0.0622 | 0.7269 | 0.169 | 0.2696 |
77
+ | 0.0684 | 27.0 | 1350 | 0.0622 | 0.7287 | 0.1696 | 0.2705 |
78
+ | 0.0684 | 28.0 | 1400 | 0.0621 | 0.7099 | 0.1642 | 0.2624 |
79
+ | 0.0684 | 29.0 | 1450 | 0.0621 | 0.7239 | 0.1683 | 0.2685 |
80
+ | 0.0516 | 30.0 | 1500 | 0.0621 | 0.7239 | 0.1683 | 0.2685 |
81
 
82
 
83
  ### Framework versions