muhtasham commited on
Commit
94e75bc
1 Parent(s): 6e10c6f

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +70 -0
README.md ADDED
@@ -0,0 +1,70 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ - f1
8
+ model-index:
9
+ - name: olm-bert-tiny-december-2022-target-glue-qqp
10
+ results: []
11
+ ---
12
+
13
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
14
+ should probably proofread and complete it, then remove this comment. -->
15
+
16
+ # olm-bert-tiny-december-2022-target-glue-qqp
17
+
18
+ This model is a fine-tuned version of [muhtasham/olm-bert-tiny-december-2022](https://huggingface.co/muhtasham/olm-bert-tiny-december-2022) on the None dataset.
19
+ It achieves the following results on the evaluation set:
20
+ - Loss: 0.5217
21
+ - Accuracy: 0.7433
22
+ - F1: 0.6048
23
+
24
+ ## Model description
25
+
26
+ More information needed
27
+
28
+ ## Intended uses & limitations
29
+
30
+ More information needed
31
+
32
+ ## Training and evaluation data
33
+
34
+ More information needed
35
+
36
+ ## Training procedure
37
+
38
+ ### Training hyperparameters
39
+
40
+ The following hyperparameters were used during training:
41
+ - learning_rate: 3e-05
42
+ - train_batch_size: 32
43
+ - eval_batch_size: 32
44
+ - seed: 42
45
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
46
+ - lr_scheduler_type: constant
47
+ - training_steps: 5000
48
+
49
+ ### Training results
50
+
51
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
52
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
53
+ | 0.6283 | 0.04 | 500 | 0.5955 | 0.6795 | 0.5186 |
54
+ | 0.5875 | 0.09 | 1000 | 0.5763 | 0.6972 | 0.5596 |
55
+ | 0.5791 | 0.13 | 1500 | 0.5690 | 0.6975 | 0.6011 |
56
+ | 0.5666 | 0.18 | 2000 | 0.5536 | 0.7156 | 0.5520 |
57
+ | 0.5568 | 0.22 | 2500 | 0.5447 | 0.7230 | 0.5709 |
58
+ | 0.5489 | 0.26 | 3000 | 0.5386 | 0.7281 | 0.5665 |
59
+ | 0.5465 | 0.31 | 3500 | 0.5305 | 0.7329 | 0.5917 |
60
+ | 0.5384 | 0.35 | 4000 | 0.5262 | 0.7357 | 0.6231 |
61
+ | 0.5422 | 0.4 | 4500 | 0.5207 | 0.7409 | 0.6200 |
62
+ | 0.5299 | 0.44 | 5000 | 0.5217 | 0.7433 | 0.6048 |
63
+
64
+
65
+ ### Framework versions
66
+
67
+ - Transformers 4.27.0.dev0
68
+ - Pytorch 1.13.1+cu116
69
+ - Datasets 2.9.1.dev0
70
+ - Tokenizers 0.13.2