File size: 1,712 Bytes
089f7f6
 
d4e9cae
 
089f7f6
 
d4e9cae
409a9f9
 
d4e9cae
089f7f6
 
 
 
 
 
 
 
 
 
409a9f9
089f7f6
6776130
 
089f7f6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
a61e263
6776130
 
089f7f6
 
 
 
 
 
 
c7e29bc
 
6776130
 
 
 
 
089f7f6
 
 
 
d4e9cae
089f7f6
 
 
d4e9cae
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
---
base_model: google/vit-base-patch16-224-in21k
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- image-classification
- vision
- generated_from_trainer
model-index:
- name: vit-base-beans
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# vit-base-beans

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 beans dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8530
- Accuracy: 0.8045

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0326        | 1.0   | 130  | 1.0319          | 0.6090   |
| 0.9721        | 2.0   | 260  | 0.9699          | 0.7293   |
| 0.8948        | 3.0   | 390  | 0.9060          | 0.7820   |
| 0.8524        | 4.0   | 520  | 0.8661          | 0.8045   |
| 0.866         | 5.0   | 650  | 0.8530          | 0.8045   |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.0.1+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1