Hugging Face's logo

Amna100
/
fold_1

Token Classification
Transformers
TensorBoard
Safetensors
deberta
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
Amna100 commited on
Commit
77eb693
•
1 Parent(s): 57d647b

End of training

Browse files
Files changed (2) hide show
  1. README.md +12 -19
  2. model.safetensors +1 -1
README.md CHANGED
@@ -16,22 +16,19 @@ model-index:
16
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
  should probably proofread and complete it, then remove this comment. -->
18
 
19
- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/wbresearch/FineTuning-ADE-DropOUT/runs/rw6sjeap)
20
- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/wbresearch/FineTuning-ADE-DropOUT/runs/g4pyaj7k)
21
- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/wbresearch/FineTuning-ADE-DropOUT/runs/t4il24wd)
22
- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/wbresearch/FineTuning-ADE-DropOUT/runs/qf2ywrxq)
23
- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/wbresearch/FineTuning-ADE-DropOUT/runs/9xmjfnoc)
24
  # fold_1
25
 
26
  This model is a fine-tuned version of [Amna100/PreTraining-MLM](https://huggingface.co/Amna100/PreTraining-MLM) on the None dataset.
27
  It achieves the following results on the evaluation set:
28
  - Loss: 0.0113
29
- - Precision: 0.7155
30
- - Recall: 0.7233
31
- - F1: 0.7194
32
  - Accuracy: 0.9993
33
- - Roc Auc: 0.9952
34
- - Pr Auc: 0.9999
35
 
36
  ## Model description
37
 
@@ -62,15 +59,11 @@ The following hyperparameters were used during training:
62
 
63
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Roc Auc | Pr Auc |
64
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------:|:------:|
65
- | 0.0241 | 1.0 | 632 | 0.0123 | 0.6317 | 0.6427 | 0.6371 | 0.9991 | 0.9958 | 0.9999 |
66
- | 0.0098 | 2.0 | 1264 | 0.0114 | 0.8436 | 0.6580 | 0.7393 | 0.9994 | 0.9946 | 0.9998 |
67
- | 0.0062 | 3.0 | 1896 | 0.0113 | 0.7155 | 0.7233 | 0.7194 | 0.9993 | 0.9952 | 0.9999 |
68
- | 0.0021 | 4.0 | 2528 | 0.0132 | 0.7990 | 0.6841 | 0.7371 | 0.9993 | 0.9944 | 0.9998 |
69
- | 0.0013 | 5.0 | 3160 | 0.0145 | 0.7783 | 0.7037 | 0.7391 | 0.9993 | 0.9956 | 0.9998 |
70
- | 0.001 | 6.0 | 3792 | 0.0159 | 0.7730 | 0.7495 | 0.7611 | 0.9994 | 0.9958 | 0.9998 |
71
- | 0.0004 | 7.0 | 4424 | 0.0143 | 0.7104 | 0.7908 | 0.7485 | 0.9993 | 0.9964 | 0.9999 |
72
- | 0.0002 | 8.0 | 5056 | 0.0173 | 0.8005 | 0.7255 | 0.7611 | 0.9994 | 0.9951 | 0.9999 |
73
- | 0.0002 | 9.0 | 5688 | 0.0176 | 0.7981 | 0.7233 | 0.7589 | 0.9993 | 0.9948 | 0.9999 |
74
 
75
 
76
  ### Framework versions
 
16
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
17
  should probably proofread and complete it, then remove this comment. -->
18
 
19
+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-Repeatedfold/runs/lvieenf2)
20
+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-Repeatedfold/runs/fgis28rc)
 
 
 
21
  # fold_1
22
 
23
  This model is a fine-tuned version of [Amna100/PreTraining-MLM](https://huggingface.co/Amna100/PreTraining-MLM) on the None dataset.
24
  It achieves the following results on the evaluation set:
25
  - Loss: 0.0113
26
+ - Precision: 0.8172
27
+ - Recall: 0.5823
28
+ - F1: 0.6801
29
  - Accuracy: 0.9993
30
+ - Roc Auc: 0.9933
31
+ - Pr Auc: 0.9998
32
 
33
  ## Model description
34
 
 
59
 
60
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Roc Auc | Pr Auc |
61
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------:|:------:|
62
+ | 0.0326 | 1.0 | 632 | 0.0138 | 0.6507 | 0.4668 | 0.5436 | 0.9991 | 0.9909 | 0.9998 |
63
+ | 0.0116 | 2.0 | 1264 | 0.0113 | 0.8172 | 0.5823 | 0.6801 | 0.9993 | 0.9933 | 0.9998 |
64
+ | 0.0071 | 3.0 | 1896 | 0.0131 | 0.7896 | 0.5995 | 0.6816 | 0.9993 | 0.9915 | 0.9998 |
65
+ | 0.0023 | 4.0 | 2528 | 0.0165 | 0.6275 | 0.6953 | 0.6597 | 0.9991 | 0.9899 | 0.9998 |
66
+ | 0.0013 | 5.0 | 3160 | 0.0173 | 0.7465 | 0.6585 | 0.6997 | 0.9993 | 0.9827 | 0.9996 |
 
 
 
 
67
 
68
 
69
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:7e63e0c202ee2eb1cf3b66f461c61af6d8e45a62090de019473ec2c8895c1176
3
  size 554446244
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:3de1b05294beb96cd75cd0d233fbbae2d98f53b12256bc149ddaa0296d1653a3
3
  size 554446244