Hugging Face's logo

nandakishormpai
/
t5-small-github-repo-tag-generation

Summarization
Transformers
PyTorch
TensorBoard
English
t5
text2text-generation
Generated from Trainer
documentation_tag
tag_generation
github
github_tag
tagging
github_repo
text-generation-inference
Inference Endpoints
Model card Files Metrics Community
17
nandakishormpai commited on
Commit
93963e4
•
1 Parent(s): 0385a26

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +34 -29
README.md CHANGED
@@ -16,11 +16,11 @@ should probably proofread and complete it, then remove this comment. -->
16
 
17
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
18
  It achieves the following results on the evaluation set:
19
- - Loss: 0.5366
20
- - Rouge1: 20.3802
21
- - Rouge2: 4.7145
22
- - Rougel: 18.411
23
- - Rougelsum: 18.3921
24
  - Gen Len: 19.0
25
 
26
  ## Model description
@@ -53,30 +53,35 @@ The following hyperparameters were used during training:
53
 
54
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
55
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
56
- | 1.4594 | 1.0 | 66 | 0.9943 | 3.9283 | 0.0 | 3.7797 | 3.7332 | 19.0 |
57
- | 0.9732 | 2.0 | 132 | 0.8077 | 1.3301 | 0.0 | 1.2269 | 1.2141 | 19.0 |
58
- | 0.8414 | 3.0 | 198 | 0.7334 | 4.3519 | 0.3755 | 4.2376 | 4.2974 | 19.0 |
59
- | 0.7843 | 4.0 | 264 | 0.6971 | 17.7535 | 1.5237 | 16.2304 | 16.1943 | 19.0 |
60
- | 0.7463 | 5.0 | 330 | 0.6655 | 19.3128 | 2.2678 | 16.5655 | 16.5492 | 19.0 |
61
- | 0.7182 | 6.0 | 396 | 0.6412 | 19.8633 | 3.3647 | 17.5046 | 17.4973 | 19.0 |
62
- | 0.6959 | 7.0 | 462 | 0.6286 | 20.274 | 3.1415 | 17.8527 | 17.9039 | 19.0 |
63
- | 0.6793 | 8.0 | 528 | 0.6121 | 19.9915 | 3.5137 | 18.1718 | 18.2166 | 19.0 |
64
- | 0.6666 | 9.0 | 594 | 0.6021 | 20.073 | 3.6482 | 18.3466 | 18.3829 | 19.0 |
65
- | 0.6561 | 10.0 | 660 | 0.5923 | 20.6227 | 3.8946 | 18.6466 | 18.694 | 19.0 |
66
- | 0.6471 | 11.0 | 726 | 0.5867 | 20.3914 | 4.1584 | 18.5822 | 18.5744 | 19.0 |
67
- | 0.638 | 12.0 | 792 | 0.5776 | 20.9846 | 4.6568 | 18.8597 | 18.8979 | 19.0 |
68
- | 0.6343 | 13.0 | 858 | 0.5715 | 19.7497 | 4.4363 | 18.262 | 18.2526 | 19.0 |
69
- | 0.6267 | 14.0 | 924 | 0.5670 | 19.5839 | 4.2251 | 17.9116 | 17.9491 | 19.0 |
70
- | 0.6211 | 15.0 | 990 | 0.5602 | 19.4954 | 4.4755 | 17.9726 | 17.9203 | 19.0 |
71
- | 0.6169 | 16.0 | 1056 | 0.5557 | 19.6247 | 4.2106 | 18.0385 | 18.0922 | 19.0 |
72
- | 0.6103 | 17.0 | 1122 | 0.5532 | 19.8744 | 4.4672 | 18.1794 | 18.1689 | 19.0 |
73
- | 0.6062 | 18.0 | 1188 | 0.5505 | 19.8744 | 4.3368 | 18.1794 | 18.1689 | 19.0 |
74
- | 0.6016 | 19.0 | 1254 | 0.5461 | 20.083 | 4.3446 | 18.4196 | 18.383 | 19.0 |
75
- | 0.5987 | 20.0 | 1320 | 0.5426 | 20.029 | 4.5884 | 18.189 | 18.1371 | 19.0 |
76
- | 0.5968 | 21.0 | 1386 | 0.5407 | 19.5394 | 4.0665 | 17.8456 | 17.7709 | 19.0 |
77
- | 0.5957 | 22.0 | 1452 | 0.5387 | 19.6368 | 4.5837 | 18.0482 | 18.0676 | 19.0 |
78
- | 0.5923 | 23.0 | 1518 | 0.5366 | 20.0744 | 4.8413 | 18.3513 | 18.2666 | 19.0 |
79
- | 0.588 | 24.0 | 1584 | 0.5366 | 20.3802 | 4.7145 | 18.411 | 18.3921 | 19.0 |
 
 
 
 
 
80
 
81
 
82
  ### Framework versions
 
16
 
17
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
18
  It achieves the following results on the evaluation set:
19
+ - Loss: 0.6488
20
+ - Rouge1: 25.2912
21
+ - Rouge2: 9.5617
22
+ - Rougel: 22.6455
23
+ - Rougelsum: 22.617
24
  - Gen Len: 19.0
25
 
26
  ## Model description
 
53
 
54
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
55
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
56
+ | 1.7857 | 1.0 | 66 | 1.2317 | 2.609 | 0.0 | 2.5996 | 2.6132 | 19.0 |
57
+ | 1.2147 | 2.0 | 132 | 1.0105 | 1.8041 | 0.0866 | 1.7432 | 1.7451 | 18.9848 |
58
+ | 1.0625 | 3.0 | 198 | 0.9154 | 2.5794 | 0.5266 | 2.4272 | 2.4305 | 19.0 |
59
+ | 0.9849 | 4.0 | 264 | 0.8615 | 19.2823 | 4.6729 | 17.639 | 17.6209 | 19.0 |
60
+ | 0.9363 | 5.0 | 330 | 0.8248 | 22.4371 | 5.4177 | 20.0806 | 20.1164 | 19.0 |
61
+ | 0.8995 | 6.0 | 396 | 0.7943 | 24.162 | 6.1729 | 21.3733 | 21.3621 | 19.0 |
62
+ | 0.8774 | 7.0 | 462 | 0.7736 | 24.0765 | 6.4219 | 21.2588 | 21.2715 | 19.0 |
63
+ | 0.8544 | 8.0 | 528 | 0.7558 | 24.4842 | 6.7685 | 21.8275 | 21.8459 | 19.0 |
64
+ | 0.8334 | 9.0 | 594 | 0.7416 | 25.009 | 7.8025 | 22.3227 | 22.3454 | 19.0 |
65
+ | 0.8212 | 10.0 | 660 | 0.7300 | 24.9532 | 7.9013 | 22.4275 | 22.4138 | 19.0 |
66
+ | 0.8118 | 11.0 | 726 | 0.7208 | 25.4191 | 7.8727 | 22.696 | 22.6894 | 19.0 |
67
+ | 0.7994 | 12.0 | 792 | 0.7114 | 25.4852 | 8.1776 | 22.4479 | 22.4522 | 19.0 |
68
+ | 0.7904 | 13.0 | 858 | 0.7020 | 25.4509 | 8.7603 | 22.7333 | 22.7213 | 19.0 |
69
+ | 0.7829 | 14.0 | 924 | 0.6958 | 25.0587 | 8.9197 | 22.6393 | 22.6207 | 19.0 |
70
+ | 0.7764 | 15.0 | 990 | 0.6897 | 25.0867 | 9.0392 | 22.6598 | 22.6808 | 19.0 |
71
+ | 0.7703 | 16.0 | 1056 | 0.6841 | 25.2402 | 9.3991 | 22.6384 | 22.6226 | 19.0 |
72
+ | 0.7633 | 17.0 | 1122 | 0.6781 | 25.7124 | 9.5485 | 23.0809 | 23.0677 | 19.0 |
73
+ | 0.7591 | 18.0 | 1188 | 0.6744 | 25.0679 | 9.4176 | 22.5225 | 22.4913 | 19.0 |
74
+ | 0.7553 | 19.0 | 1254 | 0.6695 | 25.3046 | 9.2343 | 22.931 | 22.8948 | 19.0 |
75
+ | 0.7514 | 20.0 | 1320 | 0.6661 | 25.3134 | 9.3234 | 22.8281 | 22.8198 | 19.0 |
76
+ | 0.746 | 21.0 | 1386 | 0.6630 | 25.3837 | 9.2876 | 22.806 | 22.7907 | 19.0 |
77
+ | 0.741 | 22.0 | 1452 | 0.6592 | 25.4751 | 9.3792 | 22.9321 | 22.9158 | 19.0 |
78
+ | 0.7404 | 23.0 | 1518 | 0.6566 | 25.5734 | 9.4539 | 23.0627 | 23.063 | 19.0 |
79
+ | 0.735 | 24.0 | 1584 | 0.6555 | 25.2529 | 9.5285 | 22.6775 | 22.6504 | 19.0 |
80
+ | 0.7334 | 25.0 | 1650 | 0.6536 | 25.2281 | 9.4984 | 22.3494 | 22.3364 | 19.0 |
81
+ | 0.7352 | 26.0 | 1716 | 0.6514 | 25.3464 | 9.7302 | 22.6918 | 22.6786 | 19.0 |
82
+ | 0.7322 | 27.0 | 1782 | 0.6502 | 25.2349 | 9.6516 | 22.6298 | 22.6005 | 19.0 |
83
+ | 0.7333 | 28.0 | 1848 | 0.6492 | 25.288 | 9.5646 | 22.6836 | 22.6629 | 19.0 |
84
+ | 0.7291 | 29.0 | 1914 | 0.6488 | 25.2912 | 9.5617 | 22.6455 | 22.617 | 19.0 |
85
 
86
 
87
  ### Framework versions