Commit
·
bfae21f
1
Parent(s):
c755946
update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,100 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: mit
|
3 |
+
base_model: facebook/bart-large-cnn
|
4 |
+
tags:
|
5 |
+
- generated_from_trainer
|
6 |
+
datasets:
|
7 |
+
- clupubhealth
|
8 |
+
metrics:
|
9 |
+
- rouge
|
10 |
+
model-index:
|
11 |
+
- name: bart-cnn-pubhealth-expanded-hi-grad
|
12 |
+
results:
|
13 |
+
- task:
|
14 |
+
name: Sequence-to-sequence Language Modeling
|
15 |
+
type: text2text-generation
|
16 |
+
dataset:
|
17 |
+
name: clupubhealth
|
18 |
+
type: clupubhealth
|
19 |
+
config: expanded
|
20 |
+
split: test
|
21 |
+
args: expanded
|
22 |
+
metrics:
|
23 |
+
- name: Rouge1
|
24 |
+
type: rouge
|
25 |
+
value: 28.8807
|
26 |
+
---
|
27 |
+
|
28 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
29 |
+
should probably proofread and complete it, then remove this comment. -->
|
30 |
+
|
31 |
+
# bart-cnn-pubhealth-expanded-hi-grad
|
32 |
+
|
33 |
+
This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the clupubhealth dataset.
|
34 |
+
It achieves the following results on the evaluation set:
|
35 |
+
- Loss: 2.1939
|
36 |
+
- Rouge1: 28.8807
|
37 |
+
- Rouge2: 8.9567
|
38 |
+
- Rougel: 19.5591
|
39 |
+
- Rougelsum: 20.6726
|
40 |
+
- Gen Len: 66.99
|
41 |
+
|
42 |
+
## Model description
|
43 |
+
|
44 |
+
More information needed
|
45 |
+
|
46 |
+
## Intended uses & limitations
|
47 |
+
|
48 |
+
More information needed
|
49 |
+
|
50 |
+
## Training and evaluation data
|
51 |
+
|
52 |
+
More information needed
|
53 |
+
|
54 |
+
## Training procedure
|
55 |
+
|
56 |
+
### Training hyperparameters
|
57 |
+
|
58 |
+
The following hyperparameters were used during training:
|
59 |
+
- learning_rate: 2e-05
|
60 |
+
- train_batch_size: 16
|
61 |
+
- eval_batch_size: 8
|
62 |
+
- seed: 42
|
63 |
+
- gradient_accumulation_steps: 950
|
64 |
+
- total_train_batch_size: 15200
|
65 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
66 |
+
- lr_scheduler_type: linear
|
67 |
+
- num_epochs: 10
|
68 |
+
|
69 |
+
### Training results
|
70 |
+
|
71 |
+
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|
72 |
+
|:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
|
73 |
+
| 3.4166 | 0.49 | 2 | 2.4019 | 22.0991 | 4.6789 | 15.1628 | 17.4382 | 75.065 |
|
74 |
+
| 3.2194 | 0.98 | 4 | 2.3372 | 25.0981 | 6.6975 | 17.4606 | 19.2018 | 71.225 |
|
75 |
+
| 3.0969 | 1.47 | 6 | 2.2979 | 26.4747 | 7.1948 | 18.2262 | 19.6241 | 67.19 |
|
76 |
+
| 3.0313 | 1.96 | 8 | 2.3038 | 26.8637 | 7.5831 | 18.2923 | 19.6327 | 66.875 |
|
77 |
+
| 2.9753 | 2.44 | 10 | 2.2976 | 27.8942 | 8.3434 | 19.095 | 20.6248 | 67.975 |
|
78 |
+
| 2.9296 | 2.93 | 12 | 2.2602 | 28.1255 | 8.6477 | 19.0575 | 20.7787 | 68.515 |
|
79 |
+
| 2.8681 | 3.42 | 14 | 2.2341 | 28.0812 | 8.598 | 19.3391 | 20.7526 | 68.285 |
|
80 |
+
| 2.867 | 3.91 | 16 | 2.2246 | 28.3624 | 8.7921 | 19.5552 | 21.1147 | 68.225 |
|
81 |
+
| 2.8157 | 4.4 | 18 | 2.2178 | 28.8197 | 8.8423 | 19.3606 | 20.698 | 69.08 |
|
82 |
+
| 2.8007 | 4.89 | 20 | 2.2149 | 28.34 | 8.5084 | 18.8293 | 20.1169 | 68.255 |
|
83 |
+
| 2.7797 | 5.38 | 22 | 2.2123 | 28.2156 | 8.4891 | 19.3472 | 20.5036 | 67.525 |
|
84 |
+
| 2.7563 | 5.87 | 24 | 2.2083 | 27.8927 | 8.3783 | 19.1194 | 20.2498 | 68.365 |
|
85 |
+
| 2.736 | 6.36 | 26 | 2.2035 | 28.2588 | 8.2345 | 18.9418 | 20.2931 | 68.335 |
|
86 |
+
| 2.7208 | 6.85 | 28 | 2.2020 | 28.2471 | 8.599 | 19.3465 | 20.5104 | 68.44 |
|
87 |
+
| 2.713 | 7.33 | 30 | 2.2022 | 28.1863 | 8.5142 | 19.194 | 20.2467 | 68.3 |
|
88 |
+
| 2.7135 | 7.82 | 32 | 2.2013 | 28.462 | 8.6346 | 19.2465 | 20.4812 | 68.195 |
|
89 |
+
| 2.6987 | 8.31 | 34 | 2.1988 | 28.9168 | 8.8888 | 19.6491 | 20.7796 | 67.275 |
|
90 |
+
| 2.6978 | 8.8 | 36 | 2.1965 | 28.7303 | 8.9879 | 19.5924 | 20.6943 | 67.31 |
|
91 |
+
| 2.6769 | 9.29 | 38 | 2.1946 | 28.7956 | 8.9652 | 19.545 | 20.7352 | 67.33 |
|
92 |
+
| 2.6821 | 9.78 | 40 | 2.1939 | 28.8807 | 8.9567 | 19.5591 | 20.6726 | 66.99 |
|
93 |
+
|
94 |
+
|
95 |
+
### Framework versions
|
96 |
+
|
97 |
+
- Transformers 4.31.0
|
98 |
+
- Pytorch 2.0.1+cu117
|
99 |
+
- Datasets 2.7.1
|
100 |
+
- Tokenizers 0.13.2
|