File size: 2,268 Bytes
99ea261 6fa5b1d 99ea261 6fa5b1d 99ea261 6fa5b1d 99ea261 6fa5b1d 99ea261 6fa5b1d 99ea261 6fa5b1d 99ea261 |
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 |
---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: image_classification
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.675
---
<!-- 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. -->
# image_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: 1.0801
- Accuracy: 0.675
## 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: 6e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 23 | 1.0917 | 0.625 |
| No log | 2.0 | 46 | 1.1605 | 0.6125 |
| No log | 3.0 | 69 | 1.0543 | 0.6375 |
| No log | 4.0 | 92 | 1.1663 | 0.6 |
| No log | 5.0 | 115 | 1.2546 | 0.5875 |
| No log | 6.0 | 138 | 1.0580 | 0.6 |
| No log | 7.0 | 161 | 1.1193 | 0.6125 |
| No log | 8.0 | 184 | 1.2297 | 0.525 |
| No log | 9.0 | 207 | 1.2295 | 0.55 |
| No log | 10.0 | 230 | 1.0842 | 0.6125 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
|