| --- |
| license: apache-2.0 |
| base_model: google/vit-large-patch16-224-in21k |
| tags: |
| - image-classification |
| - vision |
| - generated_from_trainer |
| datasets: |
| - imagefolder |
| metrics: |
| - accuracy |
| model-index: |
| - name: large |
| results: |
| - task: |
| name: Image Classification |
| type: image-classification |
| dataset: |
| name: citeseerx/ACL-fig |
| type: imagefolder |
| config: default |
| split: validation |
| args: default |
| metrics: |
| - name: Accuracy |
| type: accuracy |
| value: 0.9281437125748503 |
| --- |
| |
| <!-- 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. --> |
|
|
| # large |
|
|
| This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-patch16-224-in21k) on the citeseerx/ACL-fig dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2075 |
| - Accuracy: 0.9281 |
|
|
| ## 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: 8 |
| - eval_batch_size: 8 |
| - seed: 1337 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 5.0 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.6973 | 1.0 | 335 | 0.5066 | 0.8563 | |
| | 0.2901 | 2.0 | 670 | 0.3553 | 0.8892 | |
| | 0.2782 | 3.0 | 1005 | 0.2585 | 0.9162 | |
| | 0.1351 | 4.0 | 1340 | 0.2233 | 0.9281 | |
| | 0.1683 | 5.0 | 1675 | 0.2075 | 0.9281 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.36.0.dev0 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.14.6 |
| - Tokenizers 0.14.1 |
|
|
