eslamxm commited on
Commit
9886da0
1 Parent(s): 237151c

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +80 -0
README.md ADDED
@@ -0,0 +1,80 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ tags:
3
+ - summarization
4
+ - Arat5-base
5
+ - abstractive summarization
6
+ - ar
7
+ - xlsum
8
+ - generated_from_trainer
9
+ datasets:
10
+ - xlsum
11
+ model-index:
12
+ - name: AraT5-base-title-generation-finetune-ar-xlsum
13
+ results: []
14
+ ---
15
+
16
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
+ should probably proofread and complete it, then remove this comment. -->
18
+
19
+ # AraT5-base-title-generation-finetune-ar-xlsum
20
+
21
+ This model is a fine-tuned version of [UBC-NLP/AraT5-base-title-generation](https://huggingface.co/UBC-NLP/AraT5-base-title-generation) on the xlsum dataset.
22
+ It achieves the following results on the evaluation set:
23
+ - Loss: 4.2837
24
+ - Rouge-1: 31.55
25
+ - Rouge-2: 14.19
26
+ - Rouge-l: 27.52
27
+ - Gen Len: 18.65
28
+ - Bertscore: 74.0
29
+
30
+ ## Model description
31
+
32
+ More information needed
33
+
34
+ ## Intended uses & limitations
35
+
36
+ More information needed
37
+
38
+ ## Training and evaluation data
39
+
40
+ More information needed
41
+
42
+ ## Training procedure
43
+
44
+ ### Training hyperparameters
45
+
46
+ The following hyperparameters were used during training:
47
+ - learning_rate: 0.0005
48
+ - train_batch_size: 8
49
+ - eval_batch_size: 8
50
+ - seed: 42
51
+ - gradient_accumulation_steps: 16
52
+ - total_train_batch_size: 128
53
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
54
+ - lr_scheduler_type: linear
55
+ - lr_scheduler_warmup_steps: 250
56
+ - num_epochs: 10
57
+ - label_smoothing_factor: 0.1
58
+
59
+ ### Training results
60
+
61
+ | Training Loss | Epoch | Step | Validation Loss | Rouge-1 | Rouge-2 | Rouge-l | Gen Len | Bertscore |
62
+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:-------:|:---------:|
63
+ | 5.815 | 1.0 | 293 | 4.7437 | 27.05 | 10.49 | 23.56 | 18.03 | 72.56 |
64
+ | 5.0818 | 2.0 | 586 | 4.5004 | 28.92 | 11.97 | 25.09 | 18.61 | 73.08 |
65
+ | 4.7855 | 3.0 | 879 | 4.3910 | 29.66 | 12.57 | 25.79 | 18.58 | 73.3 |
66
+ | 4.588 | 4.0 | 1172 | 4.3469 | 30.22 | 13.05 | 26.36 | 18.59 | 73.61 |
67
+ | 4.4388 | 5.0 | 1465 | 4.3226 | 30.88 | 13.81 | 27.01 | 18.65 | 73.78 |
68
+ | 4.3162 | 6.0 | 1758 | 4.2990 | 30.9 | 13.6 | 26.92 | 18.68 | 73.78 |
69
+ | 4.2178 | 7.0 | 2051 | 4.2869 | 31.35 | 14.01 | 27.41 | 18.57 | 73.96 |
70
+ | 4.1387 | 8.0 | 2344 | 4.2794 | 31.28 | 13.98 | 27.34 | 18.6 | 73.87 |
71
+ | 4.0787 | 9.0 | 2637 | 4.2806 | 31.45 | 14.17 | 27.46 | 18.66 | 73.97 |
72
+ | 4.0371 | 10.0 | 2930 | 4.2837 | 31.55 | 14.19 | 27.52 | 18.65 | 74.0 |
73
+
74
+
75
+ ### Framework versions
76
+
77
+ - Transformers 4.20.0
78
+ - Pytorch 1.11.0+cu113
79
+ - Datasets 2.3.2
80
+ - Tokenizers 0.12.1