File size: 4,733 Bytes
6fa4a21
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- f1
model-index:
- name: 9-classifier-finetuned-padchest
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: F1
      type: f1
      value: 0.9562502564102563
---

<!-- 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. -->

# 9-classifier-finetuned-padchest

This model is a fine-tuned version of [nickmuchi/vit-finetuned-chest-xray-pneumonia](https://huggingface.co/nickmuchi/vit-finetuned-chest-xray-pneumonia) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1585
- F1: 0.9563

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.5332        | 1.0   | 18   | 0.5695          | 0.7920 |
| 0.4488        | 2.0   | 36   | 0.3419          | 0.7934 |
| 0.3259        | 3.0   | 54   | 0.2451          | 0.7934 |
| 0.2795        | 4.0   | 72   | 0.1954          | 0.9443 |
| 0.2348        | 5.0   | 90   | 0.1698          | 0.9343 |
| 0.1937        | 6.0   | 108  | 0.1829          | 0.9297 |
| 0.1851        | 7.0   | 126  | 0.1484          | 0.9454 |
| 0.1925        | 8.0   | 144  | 0.1330          | 0.9545 |
| 0.1614        | 9.0   | 162  | 0.1403          | 0.9387 |
| 0.1734        | 10.0  | 180  | 0.1221          | 0.9531 |
| 0.1697        | 11.0  | 198  | 0.1142          | 0.9524 |
| 0.1824        | 12.0  | 216  | 0.1129          | 0.9586 |
| 0.1336        | 13.0  | 234  | 0.1369          | 0.9441 |
| 0.1596        | 14.0  | 252  | 0.1181          | 0.9540 |
| 0.1474        | 15.0  | 270  | 0.1116          | 0.9646 |
| 0.1256        | 16.0  | 288  | 0.1035          | 0.9598 |
| 0.1398        | 17.0  | 306  | 0.1195          | 0.9519 |
| 0.1219        | 18.0  | 324  | 0.1123          | 0.9588 |
| 0.1114        | 19.0  | 342  | 0.1126          | 0.9586 |
| 0.1089        | 20.0  | 360  | 0.1083          | 0.9584 |
| 0.1123        | 21.0  | 378  | 0.1038          | 0.9554 |
| 0.1241        | 22.0  | 396  | 0.0927          | 0.9657 |
| 0.099         | 23.0  | 414  | 0.1397          | 0.9559 |
| 0.1025        | 24.0  | 432  | 0.1201          | 0.9584 |
| 0.1088        | 25.0  | 450  | 0.0894          | 0.9627 |
| 0.0953        | 26.0  | 468  | 0.1083          | 0.9632 |
| 0.0953        | 27.0  | 486  | 0.1061          | 0.9592 |
| 0.0831        | 28.0  | 504  | 0.1129          | 0.9570 |
| 0.0836        | 29.0  | 522  | 0.1123          | 0.9598 |
| 0.0705        | 30.0  | 540  | 0.1611          | 0.9499 |
| 0.1047        | 31.0  | 558  | 0.1191          | 0.9570 |
| 0.0803        | 32.0  | 576  | 0.1440          | 0.9563 |
| 0.0852        | 33.0  | 594  | 0.1149          | 0.9541 |
| 0.0588        | 34.0  | 612  | 0.1830          | 0.9489 |
| 0.0701        | 35.0  | 630  | 0.1475          | 0.9592 |
| 0.0607        | 36.0  | 648  | 0.1350          | 0.9627 |
| 0.0749        | 37.0  | 666  | 0.1389          | 0.9563 |
| 0.073         | 38.0  | 684  | 0.1463          | 0.9559 |
| 0.0579        | 39.0  | 702  | 0.1289          | 0.9595 |
| 0.0757        | 40.0  | 720  | 0.1585          | 0.9584 |
| 0.0538        | 41.0  | 738  | 0.1565          | 0.9588 |
| 0.0461        | 42.0  | 756  | 0.1630          | 0.9559 |
| 0.072         | 43.0  | 774  | 0.1704          | 0.9554 |
| 0.0517        | 44.0  | 792  | 0.1657          | 0.9559 |
| 0.0524        | 45.0  | 810  | 0.1358          | 0.9570 |
| 0.0569        | 46.0  | 828  | 0.1538          | 0.9533 |
| 0.0506        | 47.0  | 846  | 0.1579          | 0.9588 |
| 0.0506        | 48.0  | 864  | 0.1505          | 0.9566 |
| 0.0538        | 49.0  | 882  | 0.1593          | 0.9588 |
| 0.0532        | 50.0  | 900  | 0.1585          | 0.9563 |


### Framework versions

- Transformers 4.28.0.dev0
- Pytorch 2.0.0+cu117
- Datasets 2.18.0
- Tokenizers 0.13.3