hkivancoral
commited on
Commit
•
b389d9e
1
Parent(s):
cdc0cf9
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_adamax_0001_fold1
|
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: 0.9115191986644408
|
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_adamax_0001_fold1
|
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: 0.7494
|
36 |
+
- Accuracy: 0.9115
|
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 |
+
| 0.3678 | 1.0 | 226 | 0.3292 | 0.8614 |
|
69 |
+
| 0.2124 | 2.0 | 452 | 0.3720 | 0.8815 |
|
70 |
+
| 0.1134 | 3.0 | 678 | 0.4692 | 0.8631 |
|
71 |
+
| 0.0789 | 4.0 | 904 | 0.3549 | 0.9032 |
|
72 |
+
| 0.0454 | 5.0 | 1130 | 0.4305 | 0.9048 |
|
73 |
+
| 0.0205 | 6.0 | 1356 | 0.5024 | 0.9149 |
|
74 |
+
| 0.001 | 7.0 | 1582 | 0.5548 | 0.9065 |
|
75 |
+
| 0.0104 | 8.0 | 1808 | 0.5394 | 0.8998 |
|
76 |
+
| 0.0382 | 9.0 | 2034 | 0.5732 | 0.9149 |
|
77 |
+
| 0.0007 | 10.0 | 2260 | 0.6012 | 0.9098 |
|
78 |
+
| 0.0391 | 11.0 | 2486 | 0.5763 | 0.9082 |
|
79 |
+
| 0.0059 | 12.0 | 2712 | 0.6108 | 0.9065 |
|
80 |
+
| 0.0173 | 13.0 | 2938 | 0.5672 | 0.9115 |
|
81 |
+
| 0.017 | 14.0 | 3164 | 0.7490 | 0.8982 |
|
82 |
+
| 0.011 | 15.0 | 3390 | 0.6808 | 0.9065 |
|
83 |
+
| 0.0001 | 16.0 | 3616 | 0.6376 | 0.9115 |
|
84 |
+
| 0.01 | 17.0 | 3842 | 0.6232 | 0.9065 |
|
85 |
+
| 0.001 | 18.0 | 4068 | 0.6761 | 0.8982 |
|
86 |
+
| 0.0042 | 19.0 | 4294 | 0.7354 | 0.9115 |
|
87 |
+
| 0.0001 | 20.0 | 4520 | 0.6861 | 0.9098 |
|
88 |
+
| 0.0007 | 21.0 | 4746 | 0.7202 | 0.9065 |
|
89 |
+
| 0.0044 | 22.0 | 4972 | 0.6969 | 0.9082 |
|
90 |
+
| 0.0048 | 23.0 | 5198 | 0.6620 | 0.9199 |
|
91 |
+
| 0.0 | 24.0 | 5424 | 0.7820 | 0.8998 |
|
92 |
+
| 0.0 | 25.0 | 5650 | 0.6630 | 0.9149 |
|
93 |
+
| 0.0 | 26.0 | 5876 | 0.6962 | 0.9165 |
|
94 |
+
| 0.0 | 27.0 | 6102 | 0.7046 | 0.9149 |
|
95 |
+
| 0.0119 | 28.0 | 6328 | 0.8033 | 0.9032 |
|
96 |
+
| 0.0 | 29.0 | 6554 | 0.6906 | 0.9115 |
|
97 |
+
| 0.0002 | 30.0 | 6780 | 0.6827 | 0.9098 |
|
98 |
+
| 0.0002 | 31.0 | 7006 | 0.7730 | 0.9065 |
|
99 |
+
| 0.0 | 32.0 | 7232 | 0.8017 | 0.9015 |
|
100 |
+
| 0.004 | 33.0 | 7458 | 0.7703 | 0.9098 |
|
101 |
+
| 0.0001 | 34.0 | 7684 | 0.7283 | 0.9098 |
|
102 |
+
| 0.0 | 35.0 | 7910 | 0.7503 | 0.9065 |
|
103 |
+
| 0.0 | 36.0 | 8136 | 0.7083 | 0.9149 |
|
104 |
+
| 0.0 | 37.0 | 8362 | 0.7770 | 0.9048 |
|
105 |
+
| 0.0 | 38.0 | 8588 | 0.7053 | 0.9165 |
|
106 |
+
| 0.0 | 39.0 | 8814 | 0.7150 | 0.9165 |
|
107 |
+
| 0.0 | 40.0 | 9040 | 0.7204 | 0.9182 |
|
108 |
+
| 0.0022 | 41.0 | 9266 | 0.7127 | 0.9165 |
|
109 |
+
| 0.0033 | 42.0 | 9492 | 0.7275 | 0.9149 |
|
110 |
+
| 0.0 | 43.0 | 9718 | 0.7350 | 0.9165 |
|
111 |
+
| 0.0 | 44.0 | 9944 | 0.7337 | 0.9149 |
|
112 |
+
| 0.0 | 45.0 | 10170 | 0.7372 | 0.9115 |
|
113 |
+
| 0.0002 | 46.0 | 10396 | 0.7514 | 0.9165 |
|
114 |
+
| 0.0 | 47.0 | 10622 | 0.7501 | 0.9115 |
|
115 |
+
| 0.0 | 48.0 | 10848 | 0.7502 | 0.9149 |
|
116 |
+
| 0.0 | 49.0 | 11074 | 0.7494 | 0.9098 |
|
117 |
+
| 0.0 | 50.0 | 11300 | 0.7494 | 0.9115 |
|
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 sha256:0de8c0a1bf700c904e58f201b153e28e6c5cc6306948927dc1bcab73204964bd
|
3 |
size 343133766
|