Svetlana0303 commited on
Commit
7795899
1 Parent(s): ad10f48

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +76 -0
README.md ADDED
@@ -0,0 +1,76 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: apache-2.0
3
+ tags:
4
+ - generated_from_trainer
5
+ metrics:
6
+ - accuracy
7
+ model-index:
8
+ - name: Regression_albert_NOaug_MSEloss
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
+ # Regression_albert_NOaug_MSEloss
16
+
17
+ This model is a fine-tuned version of [albert-base-v2](https://huggingface.co/albert-base-v2) on an unknown dataset.
18
+ It achieves the following results on the evaluation set:
19
+ - Loss: 0.4715
20
+ - Mse: 0.4715
21
+ - Mae: 0.6001
22
+ - R2: 0.1320
23
+ - Accuracy: 0.4737
24
+
25
+ ## Model description
26
+
27
+ More information needed
28
+
29
+ ## Intended uses & limitations
30
+
31
+ More information needed
32
+
33
+ ## Training and evaluation data
34
+
35
+ More information needed
36
+
37
+ ## Training procedure
38
+
39
+ ### Training hyperparameters
40
+
41
+ The following hyperparameters were used during training:
42
+ - learning_rate: 2e-05
43
+ - train_batch_size: 4
44
+ - eval_batch_size: 4
45
+ - seed: 42
46
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
47
+ - lr_scheduler_type: linear
48
+ - num_epochs: 15
49
+
50
+ ### Training results
51
+
52
+ | Training Loss | Epoch | Step | Validation Loss | Mse | Mae | R2 | Accuracy |
53
+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:--------:|
54
+ | No log | 1.0 | 33 | 0.2966 | 0.2966 | 0.4630 | 0.1139 | 0.7568 |
55
+ | No log | 2.0 | 66 | 0.2679 | 0.2679 | 0.4039 | 0.1995 | 0.7568 |
56
+ | No log | 3.0 | 99 | 0.4088 | 0.4088 | 0.5125 | -0.2213 | 0.5405 |
57
+ | No log | 4.0 | 132 | 0.4331 | 0.4331 | 0.5399 | -0.2939 | 0.4865 |
58
+ | No log | 5.0 | 165 | 0.3699 | 0.3699 | 0.4317 | -0.1053 | 0.6757 |
59
+ | No log | 6.0 | 198 | 0.3456 | 0.3456 | 0.4117 | -0.0325 | 0.6216 |
60
+ | No log | 7.0 | 231 | 0.3371 | 0.3371 | 0.4155 | -0.0072 | 0.6757 |
61
+ | No log | 8.0 | 264 | 0.3261 | 0.3261 | 0.3811 | 0.0256 | 0.7297 |
62
+ | No log | 9.0 | 297 | 0.2312 | 0.2312 | 0.2705 | 0.3092 | 0.8108 |
63
+ | No log | 10.0 | 330 | 0.3194 | 0.3194 | 0.3681 | 0.0457 | 0.6757 |
64
+ | No log | 11.0 | 363 | 0.3638 | 0.3638 | 0.4124 | -0.0870 | 0.6757 |
65
+ | No log | 12.0 | 396 | 0.3101 | 0.3101 | 0.3630 | 0.0734 | 0.7027 |
66
+ | No log | 13.0 | 429 | 0.2762 | 0.2762 | 0.3221 | 0.1748 | 0.7568 |
67
+ | No log | 14.0 | 462 | 0.2970 | 0.2970 | 0.3376 | 0.1126 | 0.7297 |
68
+ | No log | 15.0 | 495 | 0.3185 | 0.3185 | 0.3532 | 0.0483 | 0.7297 |
69
+
70
+
71
+ ### Framework versions
72
+
73
+ - Transformers 4.28.0
74
+ - Pytorch 2.0.0+cu118
75
+ - Datasets 2.12.0
76
+ - Tokenizers 0.13.3