Commit
•
50abc3b
1
Parent(s):
9129167
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-large-patch16-224
|
4 |
+
tags:
|
5 |
+
- generated_from_trainer
|
6 |
+
datasets:
|
7 |
+
- imagefolder
|
8 |
+
metrics:
|
9 |
+
- accuracy
|
10 |
+
model-index:
|
11 |
+
- name: smids_10x_beit_large_sgd_00001_fold5
|
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: 0.6316666666666667
|
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_10x_beit_large_sgd_00001_fold5
|
32 |
+
|
33 |
+
This model is a fine-tuned version of [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
|
34 |
+
It achieves the following results on the evaluation set:
|
35 |
+
- Loss: 0.8273
|
36 |
+
- Accuracy: 0.6317
|
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: 1e-05
|
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 |
+
| 1.2351 | 1.0 | 750 | 1.2384 | 0.335 |
|
69 |
+
| 1.188 | 2.0 | 1500 | 1.2067 | 0.3417 |
|
70 |
+
| 1.1425 | 3.0 | 2250 | 1.1794 | 0.35 |
|
71 |
+
| 1.0663 | 4.0 | 3000 | 1.1549 | 0.36 |
|
72 |
+
| 1.0302 | 5.0 | 3750 | 1.1332 | 0.3733 |
|
73 |
+
| 1.0803 | 6.0 | 4500 | 1.1133 | 0.3783 |
|
74 |
+
| 1.0194 | 7.0 | 5250 | 1.0948 | 0.395 |
|
75 |
+
| 1.041 | 8.0 | 6000 | 1.0776 | 0.4133 |
|
76 |
+
| 0.958 | 9.0 | 6750 | 1.0617 | 0.4267 |
|
77 |
+
| 0.9328 | 10.0 | 7500 | 1.0465 | 0.44 |
|
78 |
+
| 0.9293 | 11.0 | 8250 | 1.0324 | 0.4533 |
|
79 |
+
| 0.9087 | 12.0 | 9000 | 1.0189 | 0.465 |
|
80 |
+
| 0.9387 | 13.0 | 9750 | 1.0063 | 0.4783 |
|
81 |
+
| 0.8996 | 14.0 | 10500 | 0.9944 | 0.4933 |
|
82 |
+
| 0.8606 | 15.0 | 11250 | 0.9830 | 0.5083 |
|
83 |
+
| 0.8536 | 16.0 | 12000 | 0.9723 | 0.5117 |
|
84 |
+
| 0.8222 | 17.0 | 12750 | 0.9621 | 0.5217 |
|
85 |
+
| 0.8298 | 18.0 | 13500 | 0.9525 | 0.53 |
|
86 |
+
| 0.9106 | 19.0 | 14250 | 0.9434 | 0.54 |
|
87 |
+
| 0.8462 | 20.0 | 15000 | 0.9347 | 0.5483 |
|
88 |
+
| 0.8209 | 21.0 | 15750 | 0.9265 | 0.5533 |
|
89 |
+
| 0.8393 | 22.0 | 16500 | 0.9186 | 0.5583 |
|
90 |
+
| 0.8236 | 23.0 | 17250 | 0.9111 | 0.565 |
|
91 |
+
| 0.8476 | 24.0 | 18000 | 0.9042 | 0.5717 |
|
92 |
+
| 0.7925 | 25.0 | 18750 | 0.8975 | 0.5733 |
|
93 |
+
| 0.8294 | 26.0 | 19500 | 0.8913 | 0.5817 |
|
94 |
+
| 0.7415 | 27.0 | 20250 | 0.8856 | 0.585 |
|
95 |
+
| 0.8113 | 28.0 | 21000 | 0.8800 | 0.585 |
|
96 |
+
| 0.8087 | 29.0 | 21750 | 0.8747 | 0.5833 |
|
97 |
+
| 0.8087 | 30.0 | 22500 | 0.8698 | 0.59 |
|
98 |
+
| 0.7723 | 31.0 | 23250 | 0.8652 | 0.595 |
|
99 |
+
| 0.7864 | 32.0 | 24000 | 0.8609 | 0.6033 |
|
100 |
+
| 0.7882 | 33.0 | 24750 | 0.8569 | 0.6083 |
|
101 |
+
| 0.7814 | 34.0 | 25500 | 0.8532 | 0.61 |
|
102 |
+
| 0.8053 | 35.0 | 26250 | 0.8498 | 0.6117 |
|
103 |
+
| 0.7759 | 36.0 | 27000 | 0.8467 | 0.6167 |
|
104 |
+
| 0.73 | 37.0 | 27750 | 0.8438 | 0.6167 |
|
105 |
+
| 0.8437 | 38.0 | 28500 | 0.8412 | 0.6183 |
|
106 |
+
| 0.7621 | 39.0 | 29250 | 0.8389 | 0.6183 |
|
107 |
+
| 0.719 | 40.0 | 30000 | 0.8367 | 0.6217 |
|
108 |
+
| 0.7491 | 41.0 | 30750 | 0.8348 | 0.625 |
|
109 |
+
| 0.7887 | 42.0 | 31500 | 0.8332 | 0.625 |
|
110 |
+
| 0.8254 | 43.0 | 32250 | 0.8317 | 0.625 |
|
111 |
+
| 0.7337 | 44.0 | 33000 | 0.8305 | 0.6267 |
|
112 |
+
| 0.7762 | 45.0 | 33750 | 0.8295 | 0.6283 |
|
113 |
+
| 0.7277 | 46.0 | 34500 | 0.8286 | 0.6317 |
|
114 |
+
| 0.7733 | 47.0 | 35250 | 0.8280 | 0.6317 |
|
115 |
+
| 0.7249 | 48.0 | 36000 | 0.8276 | 0.6317 |
|
116 |
+
| 0.7591 | 49.0 | 36750 | 0.8274 | 0.6317 |
|
117 |
+
| 0.7103 | 50.0 | 37500 | 0.8273 | 0.6317 |
|
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 1213785638
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:c6b61e0abaf8e77cf62479851fbc4696875f75f9bc5779afaddc7f399f5bcc1d
|
3 |
size 1213785638
|