File size: 1,982 Bytes
d6c4f48
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
56f59a9
d6c4f48
 
 
 
56f59a9
d6c4f48
 
 
 
 
 
 
 
 
56f59a9
 
d6c4f48
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
4693260
402cc76
 
d6c4f48
 
 
56f59a9
d6c4f48
 
 
 
 
56f59a9
 
 
 
 
d6c4f48
 
 
 
 
 
 
 
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
69
70
71
72
73
74
75
76
77
78
79
80
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: emotion_classification
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train[:600]
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.15833333333333333
---

<!-- 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. -->

# emotion_classification

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 imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8191
- Accuracy: 0.1583

## 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: 0.001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 8    | 1.8607          | 0.125    |
| No log        | 2.0   | 16   | 1.8180          | 0.1833   |
| No log        | 3.0   | 24   | 1.7982          | 0.1667   |
| No log        | 4.0   | 32   | 1.8021          | 0.1583   |
| No log        | 5.0   | 40   | 1.8006          | 0.1083   |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3