File size: 3,128 Bytes
51da4b1 02349a8 51da4b1 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 |
---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
datasets:
- food101
metrics:
- accuracy
model-index:
- name: vit-base-food101-demo-v5
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: food101
type: food101
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.8558811881188119
- task:
type: image-classification
name: Image Classification
dataset:
name: food101
type: food101
config: default
split: validation
metrics:
- name: Accuracy
type: accuracy
value: 0.7952079207920792
verified: true
- name: Precision Macro
type: precision
value: 0.8087208389002668
verified: true
- name: Precision Micro
type: precision
value: 0.7952079207920792
verified: true
- name: Precision Weighted
type: precision
value: 0.8087208389002665
verified: true
- name: Recall Macro
type: recall
value: 0.7952079207920792
verified: true
- name: Recall Micro
type: recall
value: 0.7952079207920792
verified: true
- name: Recall Weighted
type: recall
value: 0.7952079207920792
verified: true
- name: F1 Macro
type: f1
value: 0.7971943899991044
verified: true
- name: F1 Micro
type: f1
value: 0.7952079207920791
verified: true
- name: F1 Weighted
type: f1
value: 0.7971943899991044
verified: true
- name: loss
type: loss
value: 0.7573962807655334
verified: true
---
<!-- 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-food101-demo-v5
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 food101 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5434
- Accuracy: 0.8559
## 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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.6283 | 1.0 | 4735 | 0.9875 | 0.7409 |
| 0.9874 | 2.0 | 9470 | 0.7967 | 0.7894 |
| 0.7102 | 3.0 | 14205 | 0.6455 | 0.8255 |
| 0.4917 | 4.0 | 18940 | 0.5502 | 0.8524 |
### Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.1
- Tokenizers 0.12.1
|