DunnBC22 commited on
Commit
3684006
1 Parent(s): 9cb4fde

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +63 -0
README.md ADDED
@@ -0,0 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - rouge
7
+ model-index:
8
+ - name: flan-t5-base-text_summarization_data
9
+ results: []
10
+ ---
11
+
12
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
13
+ should probably proofread and complete it, then remove this comment. -->
14
+
15
+ # flan-t5-base-text_summarization_data
16
+
17
+ This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on the None dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 1.7386
20
+ - Rouge1: 43.6615
21
+ - Rouge2: 20.349
22
+ - Rougel: 40.1032
23
+ - Rougelsum: 40.1589
24
+ - Gen Len: 14.6434
25
+
26
+ ## Model description
27
+
28
+ More information needed
29
+
30
+ ## Intended uses & limitations
31
+
32
+ More information needed
33
+
34
+ ## Training and evaluation data
35
+
36
+ More information needed
37
+
38
+ ## Training procedure
39
+
40
+ ### Training hyperparameters
41
+
42
+ The following hyperparameters were used during training:
43
+ - learning_rate: 2e-05
44
+ - train_batch_size: 16
45
+ - eval_batch_size: 16
46
+ - seed: 42
47
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
48
+ - lr_scheduler_type: linear
49
+ - num_epochs: 1
50
+
51
+ ### Training results
52
+
53
+ | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
54
+ |:-------------:|:-----:|:----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
55
+ | 2.0287 | 1.0 | 1197 | 1.7386 | 43.6615 | 20.349 | 40.1032 | 40.1589 | 14.6434 |
56
+
57
+
58
+ ### Framework versions
59
+
60
+ - Transformers 4.26.1
61
+ - Pytorch 1.12.1
62
+ - Datasets 2.9.0
63
+ - Tokenizers 0.12.1