Hugging Face's logo

Nicole-M
/
Dataset1-SwinV2

Image Classification
Safetensors
swinv2
breast cancer
Generated from Trainer
Model card Files Community
Nicole-M commited on
Commit
8df0b8c
·
verified ·
1 Parent(s): 4821d19

SwinV2-finetuned

Browse files
Files changed (3) hide show
  1. README.md +21 -16
  2. model.safetensors +1 -1
  3. training_args.bin +1 -1
README.md CHANGED
@@ -1,10 +1,14 @@
1
  ---
2
- license: apache-2.0
3
- base_model: microsoft/swinv2-base-patch4-window8-256
4
  tags:
 
 
5
  - generated_from_trainer
6
  metrics:
7
  - accuracy
 
 
 
8
  model-index:
9
  - name: swinV2-Mammmogram-V1
10
  results: []
@@ -15,10 +19,13 @@ should probably proofread and complete it, then remove this comment. -->
15
 
16
  # swinV2-Mammmogram-V1
17
 
18
- This model is a fine-tuned version of [microsoft/swinv2-base-patch4-window8-256](https://huggingface.co/microsoft/swinv2-base-patch4-window8-256) on an unknown dataset.
19
  It achieves the following results on the evaluation set:
20
- - Loss: 0.1057
21
- - Accuracy: 0.9691
 
 
 
22
 
23
  ## Model description
24
 
@@ -43,24 +50,22 @@ The following hyperparameters were used during training:
43
  - seed: 42
44
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
45
  - lr_scheduler_type: linear
46
- - num_epochs: 6
47
- - mixed_precision_training: Native AMP
48
 
49
  ### Training results
50
 
51
- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
52
- |:-------------:|:-----:|:-----:|:---------------:|:--------:|
53
- | 0.549 | 1.0 | 1823 | 0.5326 | 0.7283 |
54
- | 0.3398 | 2.0 | 3646 | 0.4005 | 0.7953 |
55
- | 0.1833 | 3.0 | 5469 | 0.2375 | 0.8993 |
56
- | 0.1374 | 4.0 | 7292 | 0.1703 | 0.9291 |
57
- | 0.1574 | 5.0 | 9115 | 0.1146 | 0.9625 |
58
- | 0.1222 | 6.0 | 10938 | 0.1057 | 0.9691 |
59
 
60
 
61
  ### Framework versions
62
 
63
  - Transformers 4.42.4
64
  - Pytorch 2.3.1+cu121
65
- - Datasets 2.20.0
66
  - Tokenizers 0.19.1
 
1
  ---
2
+ base_model: swinv2
 
3
  tags:
4
+ - image-classification
5
+ - breast cancer
6
  - generated_from_trainer
7
  metrics:
8
  - accuracy
9
+ - precision
10
+ - recall
11
+ - f1
12
  model-index:
13
  - name: swinV2-Mammmogram-V1
14
  results: []
 
19
 
20
  # swinV2-Mammmogram-V1
21
 
22
+ This model is a fine-tuned version of [swinv2](https://huggingface.co/swinv2) on the Mammogram V1 dataset.
23
  It achieves the following results on the evaluation set:
24
+ - Loss: 0.1434
25
+ - Accuracy: 0.9524
26
+ - Precision: 0.9751
27
+ - Recall: 0.9524
28
+ - F1: 0.9630
29
 
30
  ## Model description
31
 
 
50
  - seed: 42
51
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
52
  - lr_scheduler_type: linear
53
+ - num_epochs: 5
 
54
 
55
  ### Training results
56
 
57
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
58
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
59
+ | 0.4455 | 1.0 | 1112 | 0.1385 | 0.9782 | 0.9739 | 0.9782 | 0.9760 |
60
+ | 0.3974 | 2.0 | 2224 | 0.1974 | 0.9524 | 0.9749 | 0.9524 | 0.9630 |
61
+ | 0.3712 | 3.0 | 3336 | 0.1386 | 0.9735 | 0.9748 | 0.9735 | 0.9741 |
62
+ | 0.2748 | 4.0 | 4448 | 0.1597 | 0.9479 | 0.9752 | 0.9479 | 0.9607 |
63
+ | 0.2603 | 5.0 | 5560 | 0.1434 | 0.9524 | 0.9751 | 0.9524 | 0.9630 |
 
64
 
65
 
66
  ### Framework versions
67
 
68
  - Transformers 4.42.4
69
  - Pytorch 2.3.1+cu121
70
+ - Datasets 2.21.0
71
  - Tokenizers 0.19.1
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:0dd21154d254c40d9bbf3e1b67f0b9624b1c60cc5cdb12d5aa5dc13fb585b71b
3
  size 347645480
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:497a4a26eb527fd7af8386e5c0808836e90c08c38ed42c6c59e929b9f21548d4
3
  size 347645480
training_args.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:f3b2e4a7260ccc71fe1830000792df4781252f6f73957b493e7e68c4ccdfc6b2
3
  size 5112
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a665139c475205bd10acd583eb537590a675255fd294c1b1068498707fbedb4c
3
  size 5112