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: hushem_40x_beit_base_f2
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.7555555555555555
hushem_40x_beit_base_f2
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: 1.7078
- Accuracy: 0.7556
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
|---|---|---|---|---|
| 0.0596 | 1.0 | 107 | 1.1201 | 0.7333 |
| 0.0359 | 2.0 | 214 | 1.2931 | 0.7778 |
| 0.0216 | 2.99 | 321 | 1.0533 | 0.8 |
| 0.0167 | 4.0 | 429 | 1.8378 | 0.6667 |
| 0.0012 | 5.0 | 536 | 1.2704 | 0.8222 |
| 0.0008 | 6.0 | 643 | 1.5019 | 0.7778 |
| 0.0001 | 6.99 | 750 | 1.6378 | 0.7111 |
| 0.0 | 8.0 | 858 | 1.6578 | 0.7333 |
| 0.0001 | 9.0 | 965 | 1.7710 | 0.7556 |
| 0.0001 | 9.98 | 1070 | 1.7078 | 0.7556 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1