eugenecamus commited on
Commit
0c57bdd
1 Parent(s): 3c0153e

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +5 -11
README.md CHANGED
@@ -1,7 +1,5 @@
1
  ---
2
  tags:
3
- - image-classification
4
- - vision
5
  - generated_from_trainer
6
  datasets:
7
  - beans
@@ -20,7 +18,7 @@ model-index:
20
  metrics:
21
  - name: Accuracy
22
  type: accuracy
23
- value: 0.9699248120300752
24
  ---
25
 
26
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,8 +28,8 @@ should probably proofread and complete it, then remove this comment. -->
30
 
31
  This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the beans dataset.
32
  It achieves the following results on the evaluation set:
33
- - Loss: 0.1014
34
- - Accuracy: 0.9699
35
 
36
  ## Model description
37
 
@@ -57,17 +55,13 @@ The following hyperparameters were used during training:
57
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
58
  - lr_scheduler_type: cosine
59
  - lr_scheduler_warmup_ratio: 0.1
60
- - num_epochs: 5.0
61
 
62
  ### Training results
63
 
64
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
65
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
66
- | 0.9524 | 1.0 | 130 | 0.2826 | 0.8647 |
67
- | 0.3596 | 2.0 | 260 | 0.2216 | 0.9023 |
68
- | 0.2419 | 3.0 | 390 | 0.1324 | 0.9474 |
69
- | 0.3248 | 4.0 | 520 | 0.1124 | 0.9699 |
70
- | 0.1557 | 5.0 | 650 | 0.1014 | 0.9699 |
71
 
72
 
73
  ### Framework versions
 
1
  ---
2
  tags:
 
 
3
  - generated_from_trainer
4
  datasets:
5
  - beans
 
18
  metrics:
19
  - name: Accuracy
20
  type: accuracy
21
+ value: 0.9022556390977443
22
  ---
23
 
24
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
28
 
29
  This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the beans dataset.
30
  It achieves the following results on the evaluation set:
31
+ - Loss: 0.2188
32
+ - Accuracy: 0.9023
33
 
34
  ## Model description
35
 
 
55
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
56
  - lr_scheduler_type: cosine
57
  - lr_scheduler_warmup_ratio: 0.1
58
+ - num_epochs: 1.0
59
 
60
  ### Training results
61
 
62
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
63
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
64
+ | 0.5679 | 1.0 | 130 | 0.2188 | 0.9023 |
 
 
 
 
65
 
66
 
67
  ### Framework versions