hkivancoral
commited on
Commit
•
56f0356
1
Parent(s):
94cbae1
End of training
Browse files- README.md +125 -0
- pytorch_model.bin +1 -1
README.md
ADDED
@@ -0,0 +1,125 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
base_model: microsoft/beit-base-patch16-224
|
4 |
+
tags:
|
5 |
+
- generated_from_trainer
|
6 |
+
datasets:
|
7 |
+
- imagefolder
|
8 |
+
metrics:
|
9 |
+
- accuracy
|
10 |
+
model-index:
|
11 |
+
- name: smids_3x_beit_base_rms_0001_fold3
|
12 |
+
results:
|
13 |
+
- task:
|
14 |
+
name: Image Classification
|
15 |
+
type: image-classification
|
16 |
+
dataset:
|
17 |
+
name: imagefolder
|
18 |
+
type: imagefolder
|
19 |
+
config: default
|
20 |
+
split: test
|
21 |
+
args: default
|
22 |
+
metrics:
|
23 |
+
- name: Accuracy
|
24 |
+
type: accuracy
|
25 |
+
value: 0.855
|
26 |
+
---
|
27 |
+
|
28 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
29 |
+
should probably proofread and complete it, then remove this comment. -->
|
30 |
+
|
31 |
+
# smids_3x_beit_base_rms_0001_fold3
|
32 |
+
|
33 |
+
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset.
|
34 |
+
It achieves the following results on the evaluation set:
|
35 |
+
- Loss: 1.6713
|
36 |
+
- Accuracy: 0.855
|
37 |
+
|
38 |
+
## Model description
|
39 |
+
|
40 |
+
More information needed
|
41 |
+
|
42 |
+
## Intended uses & limitations
|
43 |
+
|
44 |
+
More information needed
|
45 |
+
|
46 |
+
## Training and evaluation data
|
47 |
+
|
48 |
+
More information needed
|
49 |
+
|
50 |
+
## Training procedure
|
51 |
+
|
52 |
+
### Training hyperparameters
|
53 |
+
|
54 |
+
The following hyperparameters were used during training:
|
55 |
+
- learning_rate: 0.0001
|
56 |
+
- train_batch_size: 32
|
57 |
+
- eval_batch_size: 32
|
58 |
+
- seed: 42
|
59 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
60 |
+
- lr_scheduler_type: linear
|
61 |
+
- lr_scheduler_warmup_ratio: 0.1
|
62 |
+
- num_epochs: 50
|
63 |
+
|
64 |
+
### Training results
|
65 |
+
|
66 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|
67 |
+
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
|
68 |
+
| 0.7637 | 1.0 | 225 | 0.7530 | 0.7217 |
|
69 |
+
| 0.5551 | 2.0 | 450 | 0.6161 | 0.7583 |
|
70 |
+
| 0.4831 | 3.0 | 675 | 0.4948 | 0.7833 |
|
71 |
+
| 0.3281 | 4.0 | 900 | 0.5414 | 0.8033 |
|
72 |
+
| 0.3506 | 5.0 | 1125 | 0.4226 | 0.815 |
|
73 |
+
| 0.3328 | 6.0 | 1350 | 0.4220 | 0.83 |
|
74 |
+
| 0.2581 | 7.0 | 1575 | 0.5786 | 0.7883 |
|
75 |
+
| 0.1949 | 8.0 | 1800 | 0.5329 | 0.8133 |
|
76 |
+
| 0.2071 | 9.0 | 2025 | 0.4652 | 0.8417 |
|
77 |
+
| 0.1906 | 10.0 | 2250 | 0.5303 | 0.82 |
|
78 |
+
| 0.1705 | 11.0 | 2475 | 0.6288 | 0.8283 |
|
79 |
+
| 0.153 | 12.0 | 2700 | 0.5236 | 0.8383 |
|
80 |
+
| 0.0688 | 13.0 | 2925 | 0.7459 | 0.8133 |
|
81 |
+
| 0.0899 | 14.0 | 3150 | 0.8275 | 0.8117 |
|
82 |
+
| 0.0904 | 15.0 | 3375 | 0.7966 | 0.8467 |
|
83 |
+
| 0.0822 | 16.0 | 3600 | 0.8714 | 0.835 |
|
84 |
+
| 0.112 | 17.0 | 3825 | 0.8906 | 0.8433 |
|
85 |
+
| 0.0635 | 18.0 | 4050 | 0.8797 | 0.835 |
|
86 |
+
| 0.0639 | 19.0 | 4275 | 0.8962 | 0.85 |
|
87 |
+
| 0.0335 | 20.0 | 4500 | 1.1500 | 0.815 |
|
88 |
+
| 0.0798 | 21.0 | 4725 | 0.9654 | 0.82 |
|
89 |
+
| 0.0508 | 22.0 | 4950 | 1.1138 | 0.8467 |
|
90 |
+
| 0.0254 | 23.0 | 5175 | 0.9088 | 0.8367 |
|
91 |
+
| 0.0398 | 24.0 | 5400 | 1.1000 | 0.83 |
|
92 |
+
| 0.083 | 25.0 | 5625 | 0.9695 | 0.8367 |
|
93 |
+
| 0.0354 | 26.0 | 5850 | 1.1614 | 0.8317 |
|
94 |
+
| 0.018 | 27.0 | 6075 | 1.1091 | 0.8533 |
|
95 |
+
| 0.0554 | 28.0 | 6300 | 1.0860 | 0.8417 |
|
96 |
+
| 0.0435 | 29.0 | 6525 | 1.0082 | 0.8533 |
|
97 |
+
| 0.0521 | 30.0 | 6750 | 1.0251 | 0.8333 |
|
98 |
+
| 0.0523 | 31.0 | 6975 | 1.1028 | 0.8267 |
|
99 |
+
| 0.0058 | 32.0 | 7200 | 1.2099 | 0.8433 |
|
100 |
+
| 0.0089 | 33.0 | 7425 | 1.4585 | 0.8383 |
|
101 |
+
| 0.0197 | 34.0 | 7650 | 1.2388 | 0.8483 |
|
102 |
+
| 0.0029 | 35.0 | 7875 | 1.3364 | 0.83 |
|
103 |
+
| 0.0016 | 36.0 | 8100 | 1.4458 | 0.8417 |
|
104 |
+
| 0.0092 | 37.0 | 8325 | 1.4004 | 0.835 |
|
105 |
+
| 0.0003 | 38.0 | 8550 | 1.4317 | 0.8417 |
|
106 |
+
| 0.0011 | 39.0 | 8775 | 1.2820 | 0.8417 |
|
107 |
+
| 0.0089 | 40.0 | 9000 | 1.5154 | 0.8417 |
|
108 |
+
| 0.0236 | 41.0 | 9225 | 1.3755 | 0.8467 |
|
109 |
+
| 0.0009 | 42.0 | 9450 | 1.6899 | 0.8517 |
|
110 |
+
| 0.0128 | 43.0 | 9675 | 1.5784 | 0.845 |
|
111 |
+
| 0.0006 | 44.0 | 9900 | 1.6022 | 0.8517 |
|
112 |
+
| 0.0002 | 45.0 | 10125 | 1.4557 | 0.8467 |
|
113 |
+
| 0.0206 | 46.0 | 10350 | 1.5017 | 0.855 |
|
114 |
+
| 0.006 | 47.0 | 10575 | 1.5387 | 0.855 |
|
115 |
+
| 0.0004 | 48.0 | 10800 | 1.6762 | 0.855 |
|
116 |
+
| 0.001 | 49.0 | 11025 | 1.7088 | 0.855 |
|
117 |
+
| 0.0003 | 50.0 | 11250 | 1.6713 | 0.855 |
|
118 |
+
|
119 |
+
|
120 |
+
### Framework versions
|
121 |
+
|
122 |
+
- Transformers 4.32.1
|
123 |
+
- Pytorch 2.1.0+cu121
|
124 |
+
- Datasets 2.12.0
|
125 |
+
- Tokenizers 0.13.2
|
pytorch_model.bin
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 343133766
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:91154a0a707e8a6f110cfe9612d47a5b75264e691602c678894166d1184e9279
|
3 |
size 343133766
|