Hugging Face's logo

texasdave2
/
flan-t5-base-samsum

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
Eval Results
text-generation-inference
Model card Files Community
1
texasdave2 commited on
Commit
8a68712
·
1 Parent(s): 3d23083

End of training

Browse files
Files changed (3) hide show
  1. README.md +30 -30
  2. config.json +1 -1
  3. generation_config.json +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
22
  metrics:
23
  - name: Rouge1
24
  type: rouge
25
- value: 47.0919
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -33,10 +33,10 @@ should probably proofread and complete it, then remove this comment. -->
33
  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset.
34
  It achieves the following results on the evaluation set:
35
  - Loss: 1.3859
36
- - Rouge1: 47.0919
37
- - Rouge2: 23.2123
38
- - Rougel: 39.2407
39
- - Rougelsum: 43.2174
40
  - Gen Len: 17.3333
41
 
42
  ## Model description
@@ -68,35 +68,35 @@ The following hyperparameters were used during training:
68
 
69
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
70
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
71
- | 1.5121 | 0.08 | 50 | 1.4287 | 46.7806 | 22.8207 | 38.9302 | 42.7835 | 16.9634 |
72
- | 1.46 | 0.16 | 100 | 1.4199 | 46.826 | 22.7844 | 39.0295 | 42.8573 | 17.2393 |
73
- | 1.4515 | 0.24 | 150 | 1.4147 | 46.6646 | 22.9602 | 38.9391 | 42.8187 | 17.1245 |
74
- | 1.4679 | 0.33 | 200 | 1.4121 | 46.8291 | 22.7922 | 39.1404 | 43.1542 | 17.3431 |
75
- | 1.451 | 0.41 | 250 | 1.4109 | 46.8103 | 23.0066 | 39.2832 | 43.2411 | 17.2686 |
76
- | 1.4434 | 0.49 | 300 | 1.4040 | 46.6321 | 22.989 | 39.3016 | 43.0997 | 16.9158 |
77
- | 1.4417 | 0.57 | 350 | 1.4007 | 46.8538 | 22.9937 | 39.2135 | 43.1728 | 17.1172 |
78
- | 1.4781 | 0.65 | 400 | 1.3952 | 46.8055 | 23.036 | 39.2961 | 43.1755 | 17.2076 |
79
- | 1.4626 | 0.73 | 450 | 1.3940 | 47.0996 | 23.2205 | 39.3007 | 43.2286 | 17.2222 |
80
- | 1.4307 | 0.81 | 500 | 1.3955 | 46.8877 | 23.1402 | 39.2634 | 43.1279 | 17.2002 |
81
- | 1.4586 | 0.9 | 550 | 1.3933 | 46.7191 | 23.1291 | 39.2437 | 43.1183 | 17.3040 |
82
- | 1.4465 | 0.98 | 600 | 1.3905 | 46.8651 | 23.29 | 39.2514 | 43.2025 | 17.3468 |
83
- | 1.381 | 1.06 | 650 | 1.3953 | 46.9166 | 22.9547 | 39.0439 | 43.1589 | 17.4066 |
84
- | 1.4125 | 1.14 | 700 | 1.3922 | 46.5286 | 23.0552 | 38.9056 | 42.9298 | 17.2381 |
85
- | 1.3667 | 1.22 | 750 | 1.3922 | 47.3239 | 23.3549 | 39.4725 | 43.518 | 17.2930 |
86
- | 1.3878 | 1.3 | 800 | 1.3953 | 46.6837 | 23.1602 | 39.2578 | 43.2195 | 17.3358 |
87
- | 1.3884 | 1.38 | 850 | 1.3931 | 46.9537 | 23.0894 | 39.1676 | 43.1687 | 17.3614 |
88
- | 1.3766 | 1.47 | 900 | 1.3898 | 46.9996 | 23.1407 | 39.2222 | 43.237 | 17.3333 |
89
- | 1.3727 | 1.55 | 950 | 1.3889 | 46.6936 | 23.0454 | 39.0579 | 42.9472 | 17.3211 |
90
- | 1.4001 | 1.63 | 1000 | 1.3859 | 47.0919 | 23.2123 | 39.2407 | 43.2174 | 17.3333 |
91
- | 1.3894 | 1.71 | 1050 | 1.3874 | 47.2229 | 23.35 | 39.4333 | 43.4876 | 17.3297 |
92
- | 1.3697 | 1.79 | 1100 | 1.3860 | 47.0872 | 23.3503 | 39.3371 | 43.3444 | 17.3504 |
93
- | 1.3886 | 1.87 | 1150 | 1.3862 | 47.0516 | 23.3487 | 39.3653 | 43.3272 | 17.3260 |
94
- | 1.4037 | 1.95 | 1200 | 1.3861 | 47.05 | 23.3672 | 39.3131 | 43.3233 | 17.3321 |
95
 
96
 
97
  ### Framework versions
98
 
99
- - Transformers 4.33.2
100
  - Pytorch 2.0.0+cu117
101
  - Datasets 2.14.5
102
  - Tokenizers 0.13.3
 
22
  metrics:
23
  - name: Rouge1
24
  type: rouge
25
+ value: 47.1046
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
33
  This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the samsum dataset.
34
  It achieves the following results on the evaluation set:
35
  - Loss: 1.3859
36
+ - Rouge1: 47.1046
37
+ - Rouge2: 23.264
38
+ - Rougel: 39.2757
39
+ - Rougelsum: 43.2598
40
  - Gen Len: 17.3333
41
 
42
  ## Model description
 
68
 
69
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
70
  |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
71
+ | 1.5121 | 0.08 | 50 | 1.4287 | 46.7868 | 22.863 | 38.971 | 42.8209 | 16.9634 |
72
+ | 1.46 | 0.16 | 100 | 1.4199 | 46.8031 | 22.8195 | 39.0708 | 42.8717 | 17.2393 |
73
+ | 1.4515 | 0.24 | 150 | 1.4147 | 46.6849 | 23.0376 | 38.9434 | 42.8344 | 17.1245 |
74
+ | 1.4679 | 0.33 | 200 | 1.4121 | 46.8756 | 22.8504 | 39.1671 | 43.1892 | 17.3431 |
75
+ | 1.451 | 0.41 | 250 | 1.4109 | 46.8572 | 23.09 | 39.2939 | 43.2955 | 17.2686 |
76
+ | 1.4434 | 0.49 | 300 | 1.4040 | 46.6829 | 23.071 | 39.3131 | 43.1432 | 16.9158 |
77
+ | 1.4417 | 0.57 | 350 | 1.4007 | 46.8637 | 23.0661 | 39.2462 | 43.1897 | 17.1172 |
78
+ | 1.4781 | 0.65 | 400 | 1.3952 | 46.8511 | 23.1134 | 39.3071 | 43.2164 | 17.2076 |
79
+ | 1.4626 | 0.73 | 450 | 1.3940 | 47.1533 | 23.2771 | 39.3094 | 43.2806 | 17.2222 |
80
+ | 1.4307 | 0.81 | 500 | 1.3955 | 46.9527 | 23.2227 | 39.2844 | 43.1903 | 17.2002 |
81
+ | 1.4586 | 0.9 | 550 | 1.3933 | 46.7523 | 23.1759 | 39.2675 | 43.1588 | 17.3040 |
82
+ | 1.4465 | 0.98 | 600 | 1.3905 | 46.855 | 23.3518 | 39.2879 | 43.2145 | 17.3468 |
83
+ | 1.381 | 1.06 | 650 | 1.3953 | 46.9719 | 22.9788 | 39.0886 | 43.1892 | 17.4066 |
84
+ | 1.4125 | 1.14 | 700 | 1.3922 | 46.535 | 23.0956 | 38.9275 | 42.9811 | 17.2381 |
85
+ | 1.3667 | 1.22 | 750 | 1.3922 | 47.3311 | 23.4123 | 39.5412 | 43.5624 | 17.2930 |
86
+ | 1.3878 | 1.3 | 800 | 1.3953 | 46.6737 | 23.2153 | 39.2982 | 43.2596 | 17.3358 |
87
+ | 1.3884 | 1.38 | 850 | 1.3931 | 46.9764 | 23.1561 | 39.1606 | 43.2115 | 17.3614 |
88
+ | 1.3766 | 1.47 | 900 | 1.3898 | 47.0466 | 23.1674 | 39.2822 | 43.293 | 17.3333 |
89
+ | 1.3727 | 1.55 | 950 | 1.3889 | 46.7311 | 23.0837 | 39.0882 | 43.0072 | 17.3211 |
90
+ | 1.4001 | 1.63 | 1000 | 1.3859 | 47.1046 | 23.264 | 39.2757 | 43.2598 | 17.3333 |
91
+ | 1.3894 | 1.71 | 1050 | 1.3874 | 47.2479 | 23.3762 | 39.4723 | 43.5241 | 17.3297 |
92
+ | 1.3697 | 1.79 | 1100 | 1.3860 | 47.1037 | 23.3894 | 39.3848 | 43.3875 | 17.3504 |
93
+ | 1.3886 | 1.87 | 1150 | 1.3862 | 47.0714 | 23.3937 | 39.4181 | 43.3841 | 17.3260 |
94
+ | 1.4037 | 1.95 | 1200 | 1.3861 | 47.0725 | 23.4085 | 39.3575 | 43.3676 | 17.3321 |
95
 
96
 
97
  ### Framework versions
98
 
99
+ - Transformers 4.33.3
100
  - Pytorch 2.0.0+cu117
101
  - Datasets 2.14.5
102
  - Tokenizers 0.13.3
config.json CHANGED
@@ -56,7 +56,7 @@
56
  },
57
  "tie_word_embeddings": false,
58
  "torch_dtype": "float32",
59
- "transformers_version": "4.33.2",
60
  "use_cache": true,
61
  "vocab_size": 32128
62
  }
 
56
  },
57
  "tie_word_embeddings": false,
58
  "torch_dtype": "float32",
59
+ "transformers_version": "4.33.3",
60
  "use_cache": true,
61
  "vocab_size": 32128
62
  }
generation_config.json CHANGED
@@ -2,5 +2,5 @@
2
  "decoder_start_token_id": 0,
3
  "eos_token_id": 1,
4
  "pad_token_id": 0,
5
- "transformers_version": "4.33.2"
6
  }
 
2
  "decoder_start_token_id": 0,
3
  "eos_token_id": 1,
4
  "pad_token_id": 0,
5
+ "transformers_version": "4.33.3"
6
  }