Hugging Face's logo

Michelvh
/
peft-flan-t5-mc-question-generation-eduqg

Text2Text Generation
Transformers
PyTorch
t5
Generated from Trainer
text-generation-inference
Inference Endpoints
Model card Files Community
Michelvh commited on
Commit
59909d2
•
1 Parent(s): 13ccf9c

peft-flan-t5-mc-question-generation-eduqg

Browse files
Files changed (1) hide show
  1. README.md +105 -0
README.md ADDED
@@ -0,0 +1,105 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ base_model: google/flan-t5-base
4
+ tags:
5
+ - generated_from_trainer
6
+ model-index:
7
+ - name: peft-flan-t5-mc-question-generation-eduqg
8
+ results: []
9
+ ---
10
+
11
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
12
+ should probably proofread and complete it, then remove this comment. -->
13
+
14
+ # peft-flan-t5-mc-question-generation-eduqg
15
+
16
+ This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
17
+ It achieves the following results on the evaluation set:
18
+ - Loss: 0.9867
19
+
20
+ ## Model description
21
+
22
+ More information needed
23
+
24
+ ## Intended uses & limitations
25
+
26
+ More information needed
27
+
28
+ ## Training and evaluation data
29
+
30
+ More information needed
31
+
32
+ ## Training procedure
33
+
34
+ ### Training hyperparameters
35
+
36
+ The following hyperparameters were used during training:
37
+ - learning_rate: 5e-05
38
+ - train_batch_size: 1
39
+ - eval_batch_size: 1
40
+ - seed: 42
41
+ - gradient_accumulation_steps: 4
42
+ - total_train_batch_size: 4
43
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
+ - lr_scheduler_type: linear
45
+ - num_epochs: 7
46
+
47
+ ### Training results
48
+
49
+ | Training Loss | Epoch | Step | Validation Loss |
50
+ |:-------------:|:-----:|:----:|:---------------:|
51
+ | 2.548 | 0.15 | 100 | 1.9606 |
52
+ | 2.0409 | 0.29 | 200 | 1.5282 |
53
+ | 1.6969 | 0.44 | 300 | 1.2851 |
54
+ | 1.4654 | 0.59 | 400 | 1.1794 |
55
+ | 1.3643 | 0.73 | 500 | 1.1358 |
56
+ | 1.3305 | 0.88 | 600 | 1.1068 |
57
+ | 1.2952 | 1.03 | 700 | 1.0873 |
58
+ | 1.211 | 1.17 | 800 | 1.0703 |
59
+ | 1.2123 | 1.32 | 900 | 1.0590 |
60
+ | 1.229 | 1.47 | 1000 | 1.0505 |
61
+ | 1.2136 | 1.61 | 1100 | 1.0464 |
62
+ | 1.1835 | 1.76 | 1200 | 1.0402 |
63
+ | 1.217 | 1.91 | 1300 | 1.0319 |
64
+ | 1.1986 | 2.05 | 1400 | 1.0300 |
65
+ | 1.1586 | 2.2 | 1500 | 1.0257 |
66
+ | 1.1634 | 2.35 | 1600 | 1.0214 |
67
+ | 1.1661 | 2.49 | 1700 | 1.0170 |
68
+ | 1.166 | 2.64 | 1800 | 1.0157 |
69
+ | 1.1663 | 2.79 | 1900 | 1.0126 |
70
+ | 1.1367 | 2.93 | 2000 | 1.0107 |
71
+ | 1.1576 | 3.08 | 2100 | 1.0100 |
72
+ | 1.1314 | 3.23 | 2200 | 1.0070 |
73
+ | 1.1198 | 3.37 | 2300 | 1.0049 |
74
+ | 1.1712 | 3.52 | 2400 | 1.0019 |
75
+ | 1.1369 | 3.67 | 2500 | 1.0028 |
76
+ | 1.1604 | 3.82 | 2600 | 1.0005 |
77
+ | 1.1101 | 3.96 | 2700 | 0.9977 |
78
+ | 1.1227 | 4.11 | 2800 | 0.9968 |
79
+ | 1.1247 | 4.26 | 2900 | 0.9963 |
80
+ | 1.1211 | 4.4 | 3000 | 0.9952 |
81
+ | 1.1398 | 4.55 | 3100 | 0.9939 |
82
+ | 1.1333 | 4.7 | 3200 | 0.9928 |
83
+ | 1.1367 | 4.84 | 3300 | 0.9918 |
84
+ | 1.1124 | 4.99 | 3400 | 0.9919 |
85
+ | 1.1298 | 5.14 | 3500 | 0.9905 |
86
+ | 1.117 | 5.28 | 3600 | 0.9904 |
87
+ | 1.1237 | 5.43 | 3700 | 0.9886 |
88
+ | 1.1016 | 5.58 | 3800 | 0.9889 |
89
+ | 1.1492 | 5.72 | 3900 | 0.9887 |
90
+ | 1.1032 | 5.87 | 4000 | 0.9882 |
91
+ | 1.0838 | 6.02 | 4100 | 0.9879 |
92
+ | 1.0807 | 6.16 | 4200 | 0.9880 |
93
+ | 1.1062 | 6.31 | 4300 | 0.9879 |
94
+ | 1.131 | 6.46 | 4400 | 0.9873 |
95
+ | 1.1159 | 6.6 | 4500 | 0.9872 |
96
+ | 1.1361 | 6.75 | 4600 | 0.9868 |
97
+ | 1.1051 | 6.9 | 4700 | 0.9867 |
98
+
99
+
100
+ ### Framework versions
101
+
102
+ - Transformers 4.33.2
103
+ - Pytorch 2.0.0
104
+ - Datasets 2.1.0
105
+ - Tokenizers 0.13.3