File size: 2,024 Bytes
fe0342c
 
 
 
9e0c7ea
fe0342c
 
 
 
 
 
 
 
 
 
 
 
 
9e0c7ea
fe0342c
9e0c7ea
 
fe0342c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
---
license: apache-2.0
base_model: facebook/convnext-base-224-22k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: idbwbase
  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. -->

# idbwbase

This model is a fine-tuned version of [facebook/convnext-base-224-22k](https://huggingface.co/facebook/convnext-base-224-22k) on the indian_food_images dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0978
- Accuracy: 0.9741

## 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: 0.0002
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.373         | 1.0   | 4709  | 0.3002          | 0.8705   |
| 0.3244        | 2.0   | 9418  | 0.2262          | 0.9044   |
| 0.2801        | 3.0   | 14127 | 0.1987          | 0.9196   |
| 0.2366        | 4.0   | 18836 | 0.1788          | 0.9345   |
| 0.2051        | 5.0   | 23545 | 0.1463          | 0.9484   |
| 0.1764        | 6.0   | 28254 | 0.1202          | 0.9593   |
| 0.1595        | 7.0   | 32963 | 0.1243          | 0.9655   |
| 0.1359        | 8.0   | 37672 | 0.1188          | 0.9659   |
| 0.1231        | 9.0   | 42381 | 0.0978          | 0.9741   |
| 0.1162        | 10.0  | 47090 | 0.1001          | 0.9761   |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2