gayanin commited on
Commit
a5c6b2e
1 Parent(s): 383bfa9

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
+ tags:
4
+ - generated_from_trainer
5
+ model-index:
6
+ - name: bart-paraphrase-pubmed-1.1
7
+ results: []
8
+ ---
9
+
10
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
11
+ should probably proofread and complete it, then remove this comment. -->
12
+
13
+ # bart-paraphrase-pubmed-1.1
14
+
15
+ This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
16
+ It achieves the following results on the evaluation set:
17
+ - Loss: 0.4236
18
+ - Rouge2 Precision: 0.8482
19
+ - Rouge2 Recall: 0.673
20
+ - Rouge2 Fmeasure: 0.7347
21
+
22
+ ## Model description
23
+
24
+ More information needed
25
+
26
+ ## Intended uses & limitations
27
+
28
+ More information needed
29
+
30
+ ## Training and evaluation data
31
+
32
+ More information needed
33
+
34
+ ## Training procedure
35
+
36
+ ### Training hyperparameters
37
+
38
+ The following hyperparameters were used during training:
39
+ - learning_rate: 2e-05
40
+ - train_batch_size: 16
41
+ - eval_batch_size: 16
42
+ - seed: 42
43
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
+ - lr_scheduler_type: linear
45
+ - num_epochs: 10
46
+ - mixed_precision_training: Native AMP
47
+
48
+ ### Training results
49
+
50
+ | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
51
+ |:-------------:|:-----:|:----:|:---------------:|:----------------:|:-------------:|:---------------:|
52
+ | 0.6534 | 1.0 | 663 | 0.4641 | 0.8448 | 0.6691 | 0.7313 |
53
+ | 0.5078 | 2.0 | 1326 | 0.4398 | 0.8457 | 0.6719 | 0.7333 |
54
+ | 0.4367 | 3.0 | 1989 | 0.4274 | 0.847 | 0.6717 | 0.7335 |
55
+ | 0.3575 | 4.0 | 2652 | 0.4149 | 0.8481 | 0.6733 | 0.735 |
56
+ | 0.3319 | 5.0 | 3315 | 0.4170 | 0.8481 | 0.6724 | 0.7343 |
57
+ | 0.3179 | 6.0 | 3978 | 0.4264 | 0.8484 | 0.6733 | 0.735 |
58
+ | 0.2702 | 7.0 | 4641 | 0.4207 | 0.8489 | 0.6732 | 0.7353 |
59
+ | 0.2606 | 8.0 | 5304 | 0.4205 | 0.8487 | 0.6725 | 0.7347 |
60
+ | 0.2496 | 9.0 | 5967 | 0.4247 | 0.8466 | 0.6717 | 0.7334 |
61
+ | 0.2353 | 10.0 | 6630 | 0.4236 | 0.8482 | 0.673 | 0.7347 |
62
+
63
+
64
+ ### Framework versions
65
+
66
+ - Transformers 4.12.3
67
+ - Pytorch 1.9.0+cu111
68
+ - Datasets 1.15.1
69
+ - Tokenizers 0.10.3