Hugging Face's logo

milinbhade1214
/
mt5-small-finetuned-arith

Summarization
Transformers
PyTorch
mt5
text2text-generation
Generated from Trainer
Inference Endpoints
Model card Files Community
milinbhade1214 commited on
Commit
112c3ee
•
1 Parent(s): a8771d3

Training complete

Browse files
Files changed (3) hide show
  1. README.md +74 -30
  2. pytorch_model.bin +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -18,11 +18,11 @@ should probably proofread and complete it, then remove this comment. -->
18
 
19
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
20
  It achieves the following results on the evaluation set:
21
- - Loss: 0.4958
22
- - Rouge1: 90.102
23
- - Rouge2: 71.0884
24
- - Rougel: 85.102
25
- - Rougelsum: 85.0
26
 
27
  ## Model description
28
 
@@ -42,37 +42,81 @@ More information needed
42
 
43
  The following hyperparameters were used during training:
44
  - learning_rate: 5.6e-05
45
- - train_batch_size: 64
46
- - eval_batch_size: 64
47
  - seed: 42
48
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
49
  - lr_scheduler_type: linear
50
- - num_epochs: 20
51
 
52
  ### Training results
53
 
54
- | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
55
- |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:------:|:---------:|
56
- | No log | 1.0 | 14 | 0.6714 | 90.102 | 71.0884 | 85.102 | 85.0 |
57
- | No log | 2.0 | 28 | 0.6356 | 90.102 | 71.0884 | 85.102 | 85.0 |
58
- | No log | 3.0 | 42 | 0.6466 | 90.102 | 71.0884 | 85.102 | 85.0 |
59
- | No log | 4.0 | 56 | 0.6675 | 90.102 | 71.0884 | 85.102 | 85.0 |
60
- | No log | 5.0 | 70 | 0.6938 | 90.102 | 71.0884 | 85.102 | 85.0 |
61
- | No log | 6.0 | 84 | 0.6666 | 90.102 | 71.0884 | 85.102 | 85.0 |
62
- | No log | 7.0 | 98 | 0.6384 | 90.102 | 71.0884 | 85.102 | 85.0 |
63
- | 1.3745 | 8.0 | 112 | 0.6573 | 90.102 | 71.0884 | 85.102 | 85.0 |
64
- | 1.3745 | 9.0 | 126 | 0.5883 | 90.102 | 71.0884 | 85.102 | 85.0 |
65
- | 1.3745 | 10.0 | 140 | 0.5444 | 90.102 | 71.0884 | 85.102 | 85.0 |
66
- | 1.3745 | 11.0 | 154 | 0.5458 | 90.102 | 71.0884 | 85.102 | 85.0 |
67
- | 1.3745 | 12.0 | 168 | 0.5312 | 90.102 | 71.0884 | 85.102 | 85.0 |
68
- | 1.3745 | 13.0 | 182 | 0.5260 | 90.102 | 71.0884 | 85.102 | 85.0 |
69
- | 1.3745 | 14.0 | 196 | 0.5085 | 90.102 | 71.0884 | 85.102 | 85.0 |
70
- | 1.3745 | 15.0 | 210 | 0.4961 | 90.102 | 71.0884 | 85.102 | 85.0 |
71
- | 1.0525 | 16.0 | 224 | 0.4998 | 90.102 | 71.0884 | 85.102 | 85.0 |
72
- | 1.0525 | 17.0 | 238 | 0.4963 | 90.102 | 71.0884 | 85.102 | 85.0 |
73
- | 1.0525 | 18.0 | 252 | 0.4993 | 90.102 | 71.0884 | 85.102 | 85.0 |
74
- | 1.0525 | 19.0 | 266 | 0.4970 | 90.102 | 71.0884 | 85.102 | 85.0 |
75
- | 1.0525 | 20.0 | 280 | 0.4958 | 90.102 | 71.0884 | 85.102 | 85.0 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
76
 
77
 
78
  ### Framework versions
 
18
 
19
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
20
  It achieves the following results on the evaluation set:
21
+ - Loss: 0.6651
22
+ - Rouge1: 90.0
23
+ - Rouge2: 70.4082
24
+ - Rougel: 85.3061
25
+ - Rougelsum: 85.102
26
 
27
  ## Model description
28
 
 
42
 
43
  The following hyperparameters were used during training:
44
  - learning_rate: 5.6e-05
45
+ - train_batch_size: 128
46
+ - eval_batch_size: 128
47
  - seed: 42
48
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
49
  - lr_scheduler_type: linear
50
+ - num_epochs: 64
51
 
52
  ### Training results
53
 
54
+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
55
+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
56
+ | No log | 1.0 | 7 | 11.7623 | 0.0 | 0.0 | 0.0 | 0.0 |
57
+ | No log | 2.0 | 14 | 11.0473 | 0.2041 | 0.0 | 0.2041 | 0.2041 |
58
+ | No log | 3.0 | 21 | 9.4965 | 0.4082 | 0.0 | 0.4082 | 0.4082 |
59
+ | No log | 4.0 | 28 | 8.3848 | 0.8673 | 0.0 | 0.8673 | 0.8673 |
60
+ | No log | 5.0 | 35 | 7.6170 | 1.7515 | 0.0 | 1.7114 | 1.6753 |
61
+ | No log | 6.0 | 42 | 7.0008 | 4.9101 | 0.0 | 4.9093 | 4.8585 |
62
+ | No log | 7.0 | 49 | 6.7836 | 8.0777 | 0.0 | 7.7956 | 7.9186 |
63
+ | 16.7453 | 8.0 | 56 | 6.6780 | 12.3572 | 0.0 | 12.1332 | 11.878 |
64
+ | 16.7453 | 9.0 | 63 | 5.2800 | 13.5863 | 0.1701 | 12.7907 | 12.8991 |
65
+ | 16.7453 | 10.0 | 70 | 4.4990 | 13.8751 | 0.1701 | 13.1962 | 13.1834 |
66
+ | 16.7453 | 11.0 | 77 | 4.3624 | 13.4276 | 0.1701 | 13.3009 | 13.2722 |
67
+ | 16.7453 | 12.0 | 84 | 4.1101 | 14.0537 | 0.3401 | 13.3534 | 13.354 |
68
+ | 16.7453 | 13.0 | 91 | 3.7171 | 14.2128 | 0.3401 | 13.4985 | 13.4888 |
69
+ | 16.7453 | 14.0 | 98 | 3.4322 | 13.9164 | 0.1701 | 13.3916 | 13.3625 |
70
+ | 16.7453 | 15.0 | 105 | 3.2408 | 13.931 | 0.3401 | 13.7998 | 13.7901 |
71
+ | 6.4188 | 16.0 | 112 | 3.0734 | 14.0816 | 0.3401 | 13.7901 | 13.7901 |
72
+ | 6.4188 | 17.0 | 119 | 2.9270 | 14.344 | 0.8242 | 14.1983 | 14.208 |
73
+ | 6.4188 | 18.0 | 126 | 2.7746 | 16.7178 | 2.4928 | 16.3946 | 16.4334 |
74
+ | 6.4188 | 19.0 | 133 | 2.6117 | 22.7164 | 7.4678 | 22.1643 | 22.1381 |
75
+ | 6.4188 | 20.0 | 140 | 2.4419 | 25.0641 | 9.4306 | 24.2861 | 24.2714 |
76
+ | 6.4188 | 21.0 | 147 | 2.2793 | 32.0373 | 13.6803 | 31.0317 | 30.8515 |
77
+ | 6.4188 | 22.0 | 154 | 2.0741 | 40.1666 | 21.0894 | 38.5458 | 38.4592 |
78
+ | 6.4188 | 23.0 | 161 | 1.8635 | 40.1133 | 21.1222 | 38.1971 | 38.1165 |
79
+ | 3.1581 | 24.0 | 168 | 1.6788 | 47.1732 | 25.3843 | 44.6854 | 44.6021 |
80
+ | 3.1581 | 25.0 | 175 | 1.5153 | 49.4894 | 27.0538 | 46.9745 | 46.8775 |
81
+ | 3.1581 | 26.0 | 182 | 1.3337 | 47.7463 | 25.9589 | 45.3779 | 45.2896 |
82
+ | 3.1581 | 27.0 | 189 | 1.1634 | 48.6608 | 26.067 | 46.293 | 46.1794 |
83
+ | 3.1581 | 28.0 | 196 | 1.0392 | 86.6181 | 65.5782 | 81.9242 | 81.8732 |
84
+ | 3.1581 | 29.0 | 203 | 0.9519 | 90.0 | 70.4082 | 85.3061 | 85.102 |
85
+ | 3.1581 | 30.0 | 210 | 0.8837 | 90.0 | 70.4082 | 85.3061 | 85.102 |
86
+ | 3.1581 | 31.0 | 217 | 0.8246 | 90.0 | 70.4082 | 85.3061 | 85.102 |
87
+ | 2.0354 | 32.0 | 224 | 0.7630 | 90.0 | 70.4082 | 85.3061 | 85.102 |
88
+ | 2.0354 | 33.0 | 231 | 0.7221 | 90.0 | 70.4082 | 85.3061 | 85.102 |
89
+ | 2.0354 | 34.0 | 238 | 0.6957 | 90.0 | 70.4082 | 85.3061 | 85.102 |
90
+ | 2.0354 | 35.0 | 245 | 0.6852 | 90.0 | 70.4082 | 85.3061 | 85.102 |
91
+ | 2.0354 | 36.0 | 252 | 0.6734 | 90.0 | 70.4082 | 85.3061 | 85.102 |
92
+ | 2.0354 | 37.0 | 259 | 0.6667 | 90.0 | 70.4082 | 85.3061 | 85.102 |
93
+ | 2.0354 | 38.0 | 266 | 0.6670 | 90.0 | 70.4082 | 85.3061 | 85.102 |
94
+ | 2.0354 | 39.0 | 273 | 0.6684 | 90.0 | 70.4082 | 85.3061 | 85.102 |
95
+ | 1.5363 | 40.0 | 280 | 0.6626 | 90.0 | 70.4082 | 85.3061 | 85.102 |
96
+ | 1.5363 | 41.0 | 287 | 0.6621 | 90.0 | 70.4082 | 85.3061 | 85.102 |
97
+ | 1.5363 | 42.0 | 294 | 0.6699 | 90.0 | 70.4082 | 85.3061 | 85.102 |
98
+ | 1.5363 | 43.0 | 301 | 0.6751 | 90.0 | 70.4082 | 85.3061 | 85.102 |
99
+ | 1.5363 | 44.0 | 308 | 0.6839 | 90.0 | 70.4082 | 85.3061 | 85.102 |
100
+ | 1.5363 | 45.0 | 315 | 0.6987 | 90.0 | 70.4082 | 85.3061 | 85.102 |
101
+ | 1.5363 | 46.0 | 322 | 0.7060 | 90.0 | 70.4082 | 85.3061 | 85.102 |
102
+ | 1.5363 | 47.0 | 329 | 0.7125 | 90.0 | 70.4082 | 85.3061 | 85.102 |
103
+ | 1.324 | 48.0 | 336 | 0.7103 | 90.0 | 70.4082 | 85.3061 | 85.102 |
104
+ | 1.324 | 49.0 | 343 | 0.7098 | 90.0 | 70.4082 | 85.3061 | 85.102 |
105
+ | 1.324 | 50.0 | 350 | 0.7088 | 90.0 | 70.4082 | 85.3061 | 85.102 |
106
+ | 1.324 | 51.0 | 357 | 0.7112 | 90.0 | 70.4082 | 85.3061 | 85.102 |
107
+ | 1.324 | 52.0 | 364 | 0.7094 | 90.0 | 70.4082 | 85.3061 | 85.102 |
108
+ | 1.324 | 53.0 | 371 | 0.7041 | 90.0 | 70.4082 | 85.3061 | 85.102 |
109
+ | 1.324 | 54.0 | 378 | 0.6939 | 90.0 | 70.4082 | 85.3061 | 85.102 |
110
+ | 1.2374 | 55.0 | 385 | 0.6843 | 90.0 | 70.4082 | 85.3061 | 85.102 |
111
+ | 1.2374 | 56.0 | 392 | 0.6791 | 90.0 | 70.4082 | 85.3061 | 85.102 |
112
+ | 1.2374 | 57.0 | 399 | 0.6755 | 90.0 | 70.4082 | 85.3061 | 85.102 |
113
+ | 1.2374 | 58.0 | 406 | 0.6715 | 90.0 | 70.4082 | 85.3061 | 85.102 |
114
+ | 1.2374 | 59.0 | 413 | 0.6661 | 90.0 | 70.4082 | 85.3061 | 85.102 |
115
+ | 1.2374 | 60.0 | 420 | 0.6639 | 90.0 | 70.4082 | 85.3061 | 85.102 |
116
+ | 1.2374 | 61.0 | 427 | 0.6629 | 90.0 | 70.4082 | 85.3061 | 85.102 |
117
+ | 1.2374 | 62.0 | 434 | 0.6635 | 90.0 | 70.4082 | 85.3061 | 85.102 |
118
+ | 1.199 | 63.0 | 441 | 0.6646 | 90.0 | 70.4082 | 85.3061 | 85.102 |
119
+ | 1.199 | 64.0 | 448 | 0.6651 | 90.0 | 70.4082 | 85.3061 | 85.102 |
120
 
121
 
122
  ### Framework versions
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:74691b18a8252899f709ebaa2e7be73b270adda48fe2b872ad5883df0c56a4ef
3
  size 1200770885
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:eddd1884f7fcc913781b3c3aeecc3cdc0f3dd63fbb8a83207d3fa9fb02bf1b77
3
  size 1200770885
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:79ca4d07a826991e6ae7cc06c49c725aad88eac5928a12926e5cc8a9331bc4b6
3
  size 4143
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:64dd580049ed00d740069f47e8ee78ed776a69697bd4ab42869e9a7d9335ee84
3
  size 4143