metadata
license: apache-2.0
base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: beit-base-patch16-224-pt22k-ft22k-finetuned-footulcer
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: 1
beit-base-patch16-224-pt22k-ft22k-finetuned-footulcer
This model is a fine-tuned version of microsoft/beit-base-patch16-224-pt22k-ft22k on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.0120
- Accuracy: 1.0
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 0.97 | 8 | 0.3613 | 0.8103 |
| 0.5337 | 1.94 | 16 | 0.1871 | 0.9483 |
| 0.2621 | 2.91 | 24 | 0.0921 | 0.9655 |
| 0.2071 | 4.0 | 33 | 0.0626 | 0.9741 |
| 0.1577 | 4.97 | 41 | 0.0316 | 0.9914 |
| 0.1577 | 5.94 | 49 | 0.0421 | 0.9828 |
| 0.1296 | 6.91 | 57 | 0.0142 | 1.0 |
| 0.1102 | 8.0 | 66 | 0.0570 | 0.9828 |
| 0.1344 | 8.97 | 74 | 0.0123 | 1.0 |
| 0.0905 | 9.7 | 80 | 0.0120 | 1.0 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2