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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: Chess_images_classifier |
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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: 0.9 |
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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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# Chess_images_classifier |
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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: 1.0591 |
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- Accuracy: 0.9 |
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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 | 1.0 | 2 | 1.7966 | 0.1 | |
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| No log | 2.0 | 4 | 1.7835 | 0.2 | |
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| No log | 3.0 | 6 | 1.7547 | 0.2667 | |
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| No log | 4.0 | 8 | 1.7069 | 0.3667 | |
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| 1.7198 | 5.0 | 10 | 1.6416 | 0.3667 | |
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| 1.7198 | 6.0 | 12 | 1.5306 | 0.4 | |
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| 1.7198 | 7.0 | 14 | 1.4958 | 0.5333 | |
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| 1.7198 | 8.0 | 16 | 1.4440 | 0.5333 | |
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| 1.7198 | 9.0 | 18 | 1.3930 | 0.6 | |
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| 1.3635 | 10.0 | 20 | 1.2984 | 0.7333 | |
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| 1.3635 | 11.0 | 22 | 1.3484 | 0.7333 | |
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| 1.3635 | 12.0 | 24 | 1.2727 | 0.8333 | |
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| 1.3635 | 13.0 | 26 | 1.1674 | 0.8333 | |
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| 1.3635 | 14.0 | 28 | 1.1443 | 0.8667 | |
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| 1.0916 | 15.0 | 30 | 1.1607 | 0.9 | |
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| 1.0916 | 16.0 | 32 | 1.1076 | 0.8667 | |
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| 1.0916 | 17.0 | 34 | 1.0670 | 0.9667 | |
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| 1.0916 | 18.0 | 36 | 1.0694 | 0.9333 | |
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| 1.0916 | 19.0 | 38 | 1.0874 | 0.9 | |
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| 0.9397 | 20.0 | 40 | 1.0591 | 0.9 | |
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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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