Hugging Face's logo

SungWei
/
my_awesome_billsum_model

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
Eval Results
text-generation-inference
Inference Endpoints
Model card Files Community
2
SungWei commited on
Commit
076f853
•
1 Parent(s): 59cb708

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +13 -12
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
22
  metrics:
23
  - name: Rouge1
24
  type: rouge
25
- value: 0.1823
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,12 +32,12 @@ should probably proofread and complete it, then remove this comment. -->
32
 
33
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset.
34
  It achieves the following results on the evaluation set:
35
- - Loss: 2.4704
36
- - Rouge1: 0.1823
37
- - Rouge2: 0.0873
38
- - Rougel: 0.1534
39
- - Rougelsum: 0.1535
40
- - Gen Len: 19.0
41
 
42
  ## Model description
43
 
@@ -62,16 +62,17 @@ The following hyperparameters were used during training:
62
  - seed: 42
63
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
64
  - lr_scheduler_type: linear
65
- - num_epochs: 4
66
 
67
  ### Training results
68
 
69
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
70
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
71
- | No log | 1.0 | 124 | 2.6597 | 0.1355 | 0.05 | 0.114 | 0.1142 | 19.0 |
72
- | No log | 2.0 | 248 | 2.5295 | 0.1577 | 0.0686 | 0.1332 | 0.1334 | 19.0 |
73
- | No log | 3.0 | 372 | 2.4850 | 0.1726 | 0.0783 | 0.1447 | 0.1449 | 19.0 |
74
- | No log | 4.0 | 496 | 2.4704 | 0.1823 | 0.0873 | 0.1534 | 0.1535 | 19.0 |
 
75
 
76
 
77
  ### Framework versions
 
22
  metrics:
23
  - name: Rouge1
24
  type: rouge
25
+ value: 0.1648
26
  ---
27
 
28
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
32
 
33
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the billsum dataset.
34
  It achieves the following results on the evaluation set:
35
+ - Loss: 2.3855
36
+ - Rouge1: 0.1648
37
+ - Rouge2: 0.0823
38
+ - Rougel: 0.1406
39
+ - Rougelsum: 0.1402
40
+ - Gen Len: 16.4718
41
 
42
  ## Model description
43
 
 
62
  - seed: 42
63
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
64
  - lr_scheduler_type: linear
65
+ - num_epochs: 5
66
 
67
  ### Training results
68
 
69
  | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
70
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
71
+ | No log | 1.0 | 124 | 2.7268 | 0.1497 | 0.0638 | 0.1259 | 0.126 | 19.0 |
72
+ | No log | 2.0 | 248 | 2.5127 | 0.1502 | 0.0647 | 0.126 | 0.1261 | 18.9234 |
73
+ | No log | 3.0 | 372 | 2.4331 | 0.151 | 0.0682 | 0.1274 | 0.1272 | 17.0081 |
74
+ | No log | 4.0 | 496 | 2.3971 | 0.1628 | 0.0786 | 0.1388 | 0.1385 | 16.7782 |
75
+ | 2.9098 | 5.0 | 620 | 2.3855 | 0.1648 | 0.0823 | 0.1406 | 0.1402 | 16.4718 |
76
 
77
 
78
  ### Framework versions