Hugging Face's logo

Bugsec
/
fine_tuned_deberta

Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
Model card Files
xet
Community
Bugsec commited on
Commit
ec9aef6
·
verified ·
1 Parent(s): 51865f0

End of training

Browse files
Files changed (1) hide show
  1. README.md +12 -11
README.md CHANGED
@@ -20,11 +20,11 @@ should probably proofread and complete it, then remove this comment. -->
20
 
21
  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
22
  It achieves the following results on the evaluation set:
23
- - Loss: 0.2193
24
- - Accuracy: 0.9437
25
- - F1: 0.9398
26
- - Precision: 0.9921
27
- - Recall: 0.8929
28
 
29
  ## Model description
30
 
@@ -52,18 +52,19 @@ The following hyperparameters were used during training:
52
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
53
  - lr_scheduler_type: linear
54
  - lr_scheduler_warmup_steps: 100
55
- - num_epochs: 5
56
  - mixed_precision_training: Native AMP
57
 
58
  ### Training results
59
 
60
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
61
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
62
- | 0.7008 | 0.96 | 17 | 0.6755 | 0.5704 | 0.2375 | 0.95 | 0.1357 |
63
- | 0.578 | 1.97 | 35 | 0.5885 | 0.6866 | 0.5822 | 0.8493 | 0.4429 |
64
- | 0.4858 | 2.99 | 53 | 0.4109 | 0.8239 | 0.8344 | 0.7778 | 0.9 |
65
- | 0.2615 | 4.0 | 71 | 0.2202 | 0.9401 | 0.9373 | 0.9695 | 0.9071 |
66
- | 0.1685 | 4.79 | 85 | 0.2193 | 0.9437 | 0.9398 | 0.9921 | 0.8929 |
 
67
 
68
 
69
  ### Framework versions
 
20
 
21
  This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
22
  It achieves the following results on the evaluation set:
23
+ - Loss: 0.2283
24
+ - Accuracy: 0.9331
25
+ - F1: 0.9272
26
+ - Precision: 1.0
27
+ - Recall: 0.8643
28
 
29
  ## Model description
30
 
 
52
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
53
  - lr_scheduler_type: linear
54
  - lr_scheduler_warmup_steps: 100
55
+ - num_epochs: 10
56
  - mixed_precision_training: Native AMP
57
 
58
  ### Training results
59
 
60
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
61
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
62
+ | 0.7017 | 0.96 | 17 | 0.6835 | 0.5352 | 0.1081 | 1.0 | 0.0571 |
63
+ | 0.6085 | 1.97 | 35 | 0.5872 | 0.6866 | 0.5822 | 0.8493 | 0.4429 |
64
+ | 0.518 | 2.99 | 53 | 0.4436 | 0.7958 | 0.8141 | 0.7384 | 0.9071 |
65
+ | 0.2366 | 4.0 | 71 | 0.2283 | 0.9331 | 0.9272 | 1.0 | 0.8643 |
66
+ | 0.1579 | 4.96 | 88 | 0.2696 | 0.9331 | 0.9294 | 0.9690 | 0.8929 |
67
+ | 0.1626 | 5.97 | 106 | 0.2726 | 0.9225 | 0.9179 | 0.9609 | 0.8786 |
68
 
69
 
70
  ### Framework versions