Hugging Face's logo

mcanoglu
/
microsoft-codebert-base-finetuned-defect-detection

Text Classification
Transformers
TensorBoard
Safetensors
roberta
Generated from Trainer
Model card Files
xet
Metrics Community
mcanoglu commited on
Commit
bb1e736
·
verified ·
1 Parent(s): cedea37

End of training

Browse files
Files changed (2) hide show
  1. README.md +16 -10
  2. model.safetensors +1 -1
README.md CHANGED
@@ -4,6 +4,9 @@ tags:
4
  - generated_from_trainer
5
  metrics:
6
  - accuracy
 
 
 
7
  model-index:
8
  - name: microsoft-codebert-base-finetuned-defect-detection
9
  results: []
@@ -16,8 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
16
 
17
  This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
18
  It achieves the following results on the evaluation set:
19
- - Loss: 0.5346
20
- - Accuracy: 0.7093
 
 
 
21
 
22
  ## Model description
23
 
@@ -39,23 +45,23 @@ The following hyperparameters were used during training:
39
  - learning_rate: 2e-05
40
  - train_batch_size: 32
41
  - eval_batch_size: 8
42
- - seed: 42
43
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
44
  - lr_scheduler_type: linear
45
- - num_epochs: 3.0
46
 
47
  ### Training results
48
 
49
- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
50
- |:-------------:|:-----:|:----:|:---------------:|:--------:|
51
- | 0.6157 | 1.0 | 997 | 0.5484 | 0.6883 |
52
- | 0.5023 | 2.0 | 1994 | 0.5381 | 0.7061 |
53
- | 0.4403 | 3.0 | 2991 | 0.5346 | 0.7093 |
54
 
55
 
56
  ### Framework versions
57
 
58
- - Transformers 4.37.0.dev0
59
  - Pytorch 2.1.2+cu121
60
  - Datasets 2.16.1
61
  - Tokenizers 0.15.0
 
4
  - generated_from_trainer
5
  metrics:
6
  - accuracy
7
+ - f1
8
+ - precision
9
+ - recall
10
  model-index:
11
  - name: microsoft-codebert-base-finetuned-defect-detection
12
  results: []
 
19
 
20
  This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
21
  It achieves the following results on the evaluation set:
22
+ - Loss: 0.5498
23
+ - Accuracy: 0.7026
24
+ - F1: 0.7299
25
+ - Precision: 0.6559
26
+ - Recall: 0.8227
27
 
28
  ## Model description
29
 
 
45
  - learning_rate: 2e-05
46
  - train_batch_size: 32
47
  - eval_batch_size: 8
48
+ - seed: 4711
49
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
  - lr_scheduler_type: linear
51
+ - num_epochs: 3
52
 
53
  ### Training results
54
 
55
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
56
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
57
+ | 0.6584 | 1.0 | 997 | 0.5554 | 0.6827 | 0.6347 | 0.7252 | 0.5642 |
58
+ | 0.5304 | 2.0 | 1994 | 0.5229 | 0.6975 | 0.7269 | 0.6502 | 0.8243 |
59
+ | 0.4572 | 3.0 | 2991 | 0.5498 | 0.7026 | 0.7299 | 0.6559 | 0.8227 |
60
 
61
 
62
  ### Framework versions
63
 
64
+ - Transformers 4.36.2
65
  - Pytorch 2.1.2+cu121
66
  - Datasets 2.16.1
67
  - Tokenizers 0.15.0
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:2a5ffbb7b392dad4efdad054c6c9067cf54f30f1e9605ca118439f781c671c25
3
  size 498612824
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a45dcae5779eaea9134e1dd721dccf12944672194eed704494ad4c73385e2722
3
  size 498612824