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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: output_dir |
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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 |
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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: 0.5875 |
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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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# output_dir |
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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: 1.2119 |
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- Accuracy: 0.5875 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: reduce_lr_on_plateau |
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- num_epochs: 41 |
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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 | 0.8 | 2 | 2.0638 | 0.1562 | |
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| No log | 2.0 | 5 | 2.0353 | 0.2 | |
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| No log | 2.8 | 7 | 1.9965 | 0.2687 | |
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| 1.9968 | 4.0 | 10 | 1.9289 | 0.3937 | |
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| 1.9968 | 4.8 | 12 | 1.8942 | 0.3125 | |
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| 1.9968 | 6.0 | 15 | 1.8054 | 0.4562 | |
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| 1.9968 | 6.8 | 17 | 1.7626 | 0.4313 | |
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| 1.7555 | 8.0 | 20 | 1.7078 | 0.4562 | |
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| 1.7555 | 8.8 | 22 | 1.6608 | 0.45 | |
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| 1.7555 | 10.0 | 25 | 1.6121 | 0.425 | |
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| 1.7555 | 10.8 | 27 | 1.5759 | 0.4813 | |
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| 1.5214 | 12.0 | 30 | 1.5340 | 0.4562 | |
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| 1.5214 | 12.8 | 32 | 1.5006 | 0.5062 | |
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| 1.5214 | 14.0 | 35 | 1.4956 | 0.4313 | |
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| 1.5214 | 14.8 | 37 | 1.4418 | 0.5125 | |
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| 1.3342 | 16.0 | 40 | 1.4236 | 0.525 | |
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| 1.3342 | 16.8 | 42 | 1.3784 | 0.55 | |
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| 1.3342 | 18.0 | 45 | 1.4367 | 0.4938 | |
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| 1.3342 | 18.8 | 47 | 1.3665 | 0.525 | |
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| 1.1553 | 20.0 | 50 | 1.3867 | 0.4813 | |
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| 1.1553 | 20.8 | 52 | 1.3536 | 0.5312 | |
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| 1.1553 | 22.0 | 55 | 1.3391 | 0.5125 | |
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| 1.1553 | 22.8 | 57 | 1.2930 | 0.5563 | |
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| 0.9972 | 24.0 | 60 | 1.2894 | 0.5375 | |
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| 0.9972 | 24.8 | 62 | 1.2802 | 0.5625 | |
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| 0.9972 | 26.0 | 65 | 1.2671 | 0.5687 | |
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| 0.9972 | 26.8 | 67 | 1.2491 | 0.5625 | |
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| 0.838 | 28.0 | 70 | 1.2907 | 0.5437 | |
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| 0.838 | 28.8 | 72 | 1.2806 | 0.5563 | |
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| 0.838 | 30.0 | 75 | 1.2228 | 0.5687 | |
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| 0.838 | 30.8 | 77 | 1.2485 | 0.575 | |
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| 0.7226 | 32.0 | 80 | 1.2777 | 0.5437 | |
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| 0.7226 | 32.8 | 82 | 1.2106 | 0.6 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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