donadelicc commited on
Commit
82475bd
1 Parent(s): 4cf989f

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +69 -0
README.md ADDED
@@ -0,0 +1,69 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: sshleifer/distilbart-cnn-6-6
4
+ tags:
5
+ - generated_from_trainer
6
+ metrics:
7
+ - rouge
8
+ model-index:
9
+ - name: nor-sum
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # nor-sum
17
+
18
+ This model is a fine-tuned version of [sshleifer/distilbart-cnn-6-6](https://huggingface.co/sshleifer/distilbart-cnn-6-6) on the None dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 2.1812
21
+ - Rouge1: 0.2552
22
+ - Rouge2: 0.0679
23
+ - Rougel: 0.1884
24
+ - Rougelsum: 0.1886
25
+ - Gen Len: 65.3086
26
+
27
+ ## Model description
28
+
29
+ More information needed
30
+
31
+ ## Intended uses & limitations
32
+
33
+ More information needed
34
+
35
+ ## Training and evaluation data
36
+
37
+ More information needed
38
+
39
+ ## Training procedure
40
+
41
+ ### Training hyperparameters
42
+
43
+ The following hyperparameters were used during training:
44
+ - learning_rate: 2e-05
45
+ - train_batch_size: 4
46
+ - eval_batch_size: 4
47
+ - seed: 42
48
+ - gradient_accumulation_steps: 2
49
+ - total_train_batch_size: 8
50
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
51
+ - lr_scheduler_type: linear
52
+ - num_epochs: 4
53
+
54
+ ### Training results
55
+
56
+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
57
+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
58
+ | 2.6231 | 1.0 | 3188 | 2.4652 | 0.2359 | 0.0563 | 0.1732 | 0.1733 | 66.1928 |
59
+ | 2.3062 | 2.0 | 6377 | 2.2798 | 0.2524 | 0.0653 | 0.1864 | 0.1864 | 66.3107 |
60
+ | 2.0817 | 3.0 | 9565 | 2.1973 | 0.2529 | 0.0675 | 0.189 | 0.1893 | 65.077 |
61
+ | 1.9776 | 4.0 | 12752 | 2.1812 | 0.2552 | 0.0679 | 0.1884 | 0.1886 | 65.3086 |
62
+
63
+
64
+ ### Framework versions
65
+
66
+ - Transformers 4.31.0
67
+ - Pytorch 2.0.1+cu118
68
+ - Datasets 2.14.1
69
+ - Tokenizers 0.13.3