Model save
Browse files- README.md +101 -0
- model.safetensors +1 -1
README.md
ADDED
@@ -0,0 +1,101 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
base_model: google/vit-base-patch16-224-in21k
|
4 |
+
tags:
|
5 |
+
- generated_from_trainer
|
6 |
+
datasets:
|
7 |
+
- webdataset
|
8 |
+
metrics:
|
9 |
+
- accuracy
|
10 |
+
- f1
|
11 |
+
- precision
|
12 |
+
- recall
|
13 |
+
model-index:
|
14 |
+
- name: vit-base-patch16-224-in21k-finetuned_v2024-7-24-frost
|
15 |
+
results:
|
16 |
+
- task:
|
17 |
+
name: Image Classification
|
18 |
+
type: image-classification
|
19 |
+
dataset:
|
20 |
+
name: webdataset
|
21 |
+
type: webdataset
|
22 |
+
config: default
|
23 |
+
split: train
|
24 |
+
args: default
|
25 |
+
metrics:
|
26 |
+
- name: Accuracy
|
27 |
+
type: accuracy
|
28 |
+
value: 0.9530973451327434
|
29 |
+
- name: F1
|
30 |
+
type: f1
|
31 |
+
value: 0.8798185941043084
|
32 |
+
- name: Precision
|
33 |
+
type: precision
|
34 |
+
value: 0.8858447488584474
|
35 |
+
- name: Recall
|
36 |
+
type: recall
|
37 |
+
value: 0.8738738738738738
|
38 |
+
---
|
39 |
+
|
40 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
41 |
+
should probably proofread and complete it, then remove this comment. -->
|
42 |
+
|
43 |
+
# vit-base-patch16-224-in21k-finetuned_v2024-7-24-frost
|
44 |
+
|
45 |
+
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the webdataset dataset.
|
46 |
+
It achieves the following results on the evaluation set:
|
47 |
+
- Loss: 0.1391
|
48 |
+
- Accuracy: 0.9531
|
49 |
+
- F1: 0.8798
|
50 |
+
- Precision: 0.8858
|
51 |
+
- Recall: 0.8739
|
52 |
+
|
53 |
+
## Model description
|
54 |
+
|
55 |
+
More information needed
|
56 |
+
|
57 |
+
## Intended uses & limitations
|
58 |
+
|
59 |
+
More information needed
|
60 |
+
|
61 |
+
## Training and evaluation data
|
62 |
+
|
63 |
+
More information needed
|
64 |
+
|
65 |
+
## Training procedure
|
66 |
+
|
67 |
+
### Training hyperparameters
|
68 |
+
|
69 |
+
The following hyperparameters were used during training:
|
70 |
+
- learning_rate: 0.0002
|
71 |
+
- train_batch_size: 16
|
72 |
+
- eval_batch_size: 8
|
73 |
+
- seed: 42
|
74 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
75 |
+
- lr_scheduler_type: linear
|
76 |
+
- lr_scheduler_warmup_ratio: 0.1
|
77 |
+
- num_epochs: 17
|
78 |
+
- mixed_precision_training: Native AMP
|
79 |
+
|
80 |
+
### Training results
|
81 |
+
|
82 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|
83 |
+
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
|
84 |
+
| 0.3281 | 1.5625 | 100 | 0.3177 | 0.9009 | 0.6957 | 0.8767 | 0.5766 |
|
85 |
+
| 0.2532 | 3.125 | 200 | 0.2424 | 0.9177 | 0.7832 | 0.8116 | 0.7568 |
|
86 |
+
| 0.1762 | 4.6875 | 300 | 0.1849 | 0.9407 | 0.8453 | 0.8673 | 0.8243 |
|
87 |
+
| 0.1525 | 6.25 | 400 | 0.1834 | 0.9257 | 0.8056 | 0.8286 | 0.7838 |
|
88 |
+
| 0.1447 | 7.8125 | 500 | 0.1612 | 0.9416 | 0.8472 | 0.8714 | 0.8243 |
|
89 |
+
| 0.1114 | 9.375 | 600 | 0.1522 | 0.9434 | 0.8545 | 0.8624 | 0.8468 |
|
90 |
+
| 0.1004 | 10.9375 | 700 | 0.1525 | 0.9451 | 0.8571 | 0.8774 | 0.8378 |
|
91 |
+
| 0.0831 | 12.5 | 800 | 0.1442 | 0.9513 | 0.8741 | 0.8884 | 0.8604 |
|
92 |
+
| 0.0654 | 14.0625 | 900 | 0.1378 | 0.9496 | 0.8690 | 0.8873 | 0.8514 |
|
93 |
+
| 0.0583 | 15.625 | 1000 | 0.1391 | 0.9531 | 0.8798 | 0.8858 | 0.8739 |
|
94 |
+
|
95 |
+
|
96 |
+
### Framework versions
|
97 |
+
|
98 |
+
- Transformers 4.42.4
|
99 |
+
- Pytorch 2.3.1+cu121
|
100 |
+
- Datasets 2.20.0
|
101 |
+
- Tokenizers 0.19.1
|
model.safetensors
CHANGED
@@ -1,3 +1,3 @@
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
-
oid sha256:
|
3 |
size 343248584
|
|
|
1 |
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:127e1abb846a26a6fd77233d8b218e9f64cb4778b63d772de076c4a190299d94
|
3 |
size 343248584
|