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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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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: computer_parts_classifier-model |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: train[:722] |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8137931034482758 |
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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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# computer_parts_classifier-model |
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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 the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5117 |
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- Accuracy: 0.8138 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 20 |
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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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| No log | 0.97 | 9 | 1.0525 | 0.5517 | |
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| 1.0645 | 1.95 | 18 | 0.9405 | 0.6 | |
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| 0.9405 | 2.92 | 27 | 0.7902 | 0.7034 | |
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| 0.7669 | 4.0 | 37 | 0.6923 | 0.7379 | |
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| 0.6008 | 4.97 | 46 | 0.6152 | 0.7862 | |
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| 0.5142 | 5.95 | 55 | 0.5639 | 0.7931 | |
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| 0.394 | 6.92 | 64 | 0.5640 | 0.8 | |
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| 0.3649 | 8.0 | 74 | 0.5181 | 0.7862 | |
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| 0.279 | 8.97 | 83 | 0.5094 | 0.8345 | |
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| 0.2549 | 9.95 | 92 | 0.4882 | 0.8276 | |
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| 0.1925 | 10.92 | 101 | 0.5041 | 0.8 | |
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| 0.2185 | 12.0 | 111 | 0.5195 | 0.8138 | |
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| 0.1921 | 12.97 | 120 | 0.5170 | 0.8 | |
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| 0.1921 | 13.95 | 129 | 0.5846 | 0.7793 | |
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| 0.15 | 14.92 | 138 | 0.5217 | 0.8207 | |
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| 0.1798 | 16.0 | 148 | 0.5421 | 0.7862 | |
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| 0.1729 | 16.97 | 157 | 0.5516 | 0.8207 | |
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| 0.1459 | 17.95 | 166 | 0.5438 | 0.7931 | |
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| 0.1701 | 18.92 | 175 | 0.5043 | 0.8345 | |
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| 0.1487 | 19.46 | 180 | 0.5117 | 0.8138 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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