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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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model-index: |
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- name: ViT-VGGFace |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# ViT-VGGFace |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4284 |
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- Accuracy: 0.6615 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 96 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:--------:| |
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| 5.1532 | 0.9982 | 416 | 5.0937 | 0.1848 | |
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| 3.8037 | 1.9988 | 833 | 3.7332 | 0.4684 | |
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| 3.0074 | 2.9994 | 1250 | 2.9895 | 0.5756 | |
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| 2.5421 | 4.0 | 1667 | 2.5881 | 0.634 | |
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| 2.4549 | 4.9910 | 2080 | 2.4284 | 0.6615 | |
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### Framework versions |
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- Transformers 4.42.4 |
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- Pytorch 2.3.1+rocm6.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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