metadata
tags:
- generated_from_trainer
datasets:
- image_folder
metrics:
- f1
model-index:
- name: vit_flyswot_test
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: image_folder
type: image_folder
args: default
metrics:
- name: F1
type: f1
value: 0.849172221610369
vit_flyswot_test
This model is a fine-tuned version of on the image_folder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4777
- F1: 0.8492
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 666
- 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 | F1 |
|---|---|---|---|---|
| No log | 1.0 | 52 | 1.2007 | 0.3533 |
| No log | 2.0 | 104 | 1.0037 | 0.5525 |
| No log | 3.0 | 156 | 0.8301 | 0.6318 |
| No log | 4.0 | 208 | 0.7224 | 0.6946 |
| No log | 5.0 | 260 | 0.7298 | 0.7145 |
| No log | 6.0 | 312 | 0.6328 | 0.7729 |
| No log | 7.0 | 364 | 0.6010 | 0.7992 |
| No log | 8.0 | 416 | 0.5174 | 0.8364 |
| No log | 9.0 | 468 | 0.5084 | 0.8479 |
| 0.6372 | 10.0 | 520 | 0.4777 | 0.8492 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.6