AKbuyer commited on
Commit
92a0bad
1 Parent(s): f0fe551

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +86 -0
README.md ADDED
@@ -0,0 +1,86 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - multi_news
7
+ metrics:
8
+ - rouge
9
+ model-index:
10
+ - name: resume6
11
+ results:
12
+ - task:
13
+ name: Sequence-to-sequence Language Modeling
14
+ type: text2text-generation
15
+ dataset:
16
+ name: multi_news
17
+ type: multi_news
18
+ config: default
19
+ split: test
20
+ args: default
21
+ metrics:
22
+ - name: Rouge1
23
+ type: rouge
24
+ value: 22.17621046093242
25
+ ---
26
+
27
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
28
+ should probably proofread and complete it, then remove this comment. -->
29
+
30
+ # resume6
31
+
32
+ This model is a fine-tuned version of [AKbuyer/resume5](https://huggingface.co/AKbuyer/resume5) on the multi_news dataset.
33
+ It achieves the following results on the evaluation set:
34
+ - Loss: 2.9796
35
+ - Rouge1: 22.1762
36
+ - Rouge2: 6.6459
37
+ - Rougel: 18.3710
38
+ - Rougelsum: 18.3626
39
+ - Gen Len: 1893.4899
40
+
41
+ ## Model description
42
+
43
+ More information needed
44
+
45
+ ## Intended uses & limitations
46
+
47
+ More information needed
48
+
49
+ ## Training and evaluation data
50
+
51
+ More information needed
52
+
53
+ ## Training procedure
54
+
55
+ ### Training hyperparameters
56
+
57
+ The following hyperparameters were used during training:
58
+ - learning_rate: 5e-07
59
+ - train_batch_size: 8
60
+ - eval_batch_size: 8
61
+ - seed: 42
62
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
63
+ - lr_scheduler_type: linear
64
+ - num_epochs: 8
65
+ - mixed_precision_training: Native AMP
66
+
67
+ ### Training results
68
+
69
+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
70
+ |:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:---------:|
71
+ | 3.3348 | 1.0 | 5622 | 3.0918 | 21.3362 | 6.1922 | 17.7104 | 17.6992 | 1893.0630 |
72
+ | 3.2854 | 2.0 | 11244 | 3.0466 | 21.6506 | 6.3791 | 17.9362 | 17.9246 | 1891.6044 |
73
+ | 3.2205 | 3.0 | 16866 | 3.0200 | 21.8475 | 6.4847 | 18.0981 | 18.0882 | 1892.4760 |
74
+ | 3.2251 | 4.0 | 22488 | 3.0029 | 22.0082 | 6.5196 | 18.2405 | 18.2301 | 1892.9385 |
75
+ | 3.2348 | 5.0 | 28110 | 2.9916 | 22.1078 | 6.5975 | 18.3134 | 18.2985 | 1893.3298 |
76
+ | 3.2257 | 6.0 | 33732 | 2.9845 | 22.1627 | 6.6119 | 18.3677 | 18.3496 | 1893.5788 |
77
+ | 3.2106 | 7.0 | 39354 | 2.9806 | 22.1825 | 6.6472 | 18.3798 | 18.3664 | 1893.5432 |
78
+ | 3.22 | 8.0 | 44976 | 2.9796 | 22.1762 | 6.6459 | 18.3710 | 18.3626 | 1893.4899 |
79
+
80
+
81
+ ### Framework versions
82
+
83
+ - Transformers 4.29.2
84
+ - Pytorch 2.0.1+cu118
85
+ - Datasets 2.12.0
86
+ - Tokenizers 0.13.3