| --- |
| tags: |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: ditmodel |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: imagefolder |
| type: imagefolder |
| config: test |
| split: train |
| args: test |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9523326572008114 |
| --- |
| |
| <!-- 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. --> |
|
|
| # ditmodel |
|
|
| This model was fintuned on DiT model for document classification on custom dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1482 |
| - Accuracy: 0.9523 |
| - Weighted f1: 0.9524 |
| - Micro f1: 0.9523 |
| - Macro f1: 0.9505 |
| - Weighted recall: 0.9523 |
| - Micro recall: 0.9523 |
| - Macro recall: 0.9523 |
| - Weighted precision: 0.9544 |
| - Micro precision: 0.9523 |
| - Macro precision: 0.9506 |
|
|
| ## 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: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:| |
| | 0.2337 | 1.0 | 78 | 0.2668 | 0.9087 | 0.9098 | 0.9087 | 0.9058 | 0.9087 | 0.9087 | 0.9040 | 0.9229 | 0.9087 | 0.9220 | |
| | 0.1711 | 2.0 | 156 | 0.1820 | 0.9376 | 0.9380 | 0.9376 | 0.9331 | 0.9376 | 0.9376 | 0.9403 | 0.9416 | 0.9376 | 0.9292 | |
| | 0.1297 | 3.0 | 234 | 0.1482 | 0.9523 | 0.9524 | 0.9523 | 0.9505 | 0.9523 | 0.9523 | 0.9523 | 0.9544 | 0.9523 | 0.9506 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.35.2 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.6.1 |
| - Tokenizers 0.15.1 |
|
|
