File size: 2,223 Bytes
a1a6284 |
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 |
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-base-beans-demo-v5
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-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).
It achieves the following results on the evaluation set:
- Loss: 0.0816
- Accuracy: 0.9819
## 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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5092 | 0.28 | 100 | 0.6420 | 0.7681 |
| 0.5076 | 0.56 | 200 | 0.4069 | 0.8722 |
| 0.3291 | 0.83 | 300 | 0.4342 | 0.8569 |
| 0.108 | 1.11 | 400 | 0.2410 | 0.9292 |
| 0.0378 | 1.39 | 500 | 0.3107 | 0.9139 |
| 0.1488 | 1.67 | 600 | 0.1984 | 0.9389 |
| 0.0532 | 1.94 | 700 | 0.1714 | 0.9514 |
| 0.0122 | 2.22 | 800 | 0.1334 | 0.9611 |
| 0.0529 | 2.5 | 900 | 0.1139 | 0.9653 |
| 0.0221 | 2.78 | 1000 | 0.0875 | 0.9736 |
| 0.0052 | 3.06 | 1100 | 0.0816 | 0.9819 |
| 0.0045 | 3.33 | 1200 | 0.0873 | 0.9792 |
| 0.0113 | 3.61 | 1300 | 0.0882 | 0.9833 |
| 0.0043 | 3.89 | 1400 | 0.0865 | 0.9806 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
|