metadata
license: apache-2.0
base_model: facebook/deit-base-patch16-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: smids_deit_base_f1
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: 0.8747913188647746
smids_deit_base_f1
This model is a fine-tuned version of facebook/deit-base-patch16-224 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.4898
- Accuracy: 0.8748
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 |
|---|---|---|---|---|
| 0.3398 | 1.0 | 375 | 0.4288 | 0.8164 |
| 0.2944 | 2.0 | 750 | 0.4228 | 0.8297 |
| 0.1957 | 3.0 | 1125 | 0.4014 | 0.8497 |
| 0.176 | 4.0 | 1501 | 0.4565 | 0.8514 |
| 0.1333 | 5.0 | 1876 | 0.3698 | 0.8731 |
| 0.1322 | 6.0 | 2251 | 0.5002 | 0.8481 |
| 0.0952 | 7.0 | 2626 | 0.4711 | 0.8648 |
| 0.0941 | 8.0 | 3002 | 0.4872 | 0.8698 |
| 0.0946 | 9.0 | 3377 | 0.5003 | 0.8564 |
| 0.0911 | 9.99 | 3750 | 0.4898 | 0.8748 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.12.0
- Tokenizers 0.13.2