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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: chessdata-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[:5000] |
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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: 0.8378378378378378 |
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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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# chessdata-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: 0.5827 |
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- Accuracy: 0.8378 |
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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 | 7 | 1.1069 | 0.7207 | |
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| 1.0143 | 2.0 | 14 | 1.0853 | 0.7117 | |
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| 0.9148 | 3.0 | 21 | 0.9472 | 0.7297 | |
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| 0.9148 | 4.0 | 28 | 0.8859 | 0.7568 | |
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| 0.7721 | 5.0 | 35 | 0.8500 | 0.7658 | |
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| 0.71 | 6.0 | 42 | 0.7973 | 0.8108 | |
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| 0.71 | 7.0 | 49 | 0.8040 | 0.7748 | |
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| 0.641 | 8.0 | 56 | 0.8344 | 0.7207 | |
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| 0.6122 | 9.0 | 63 | 0.7528 | 0.7748 | |
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| 0.5698 | 10.0 | 70 | 0.8087 | 0.7748 | |
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| 0.5698 | 11.0 | 77 | 0.7347 | 0.7838 | |
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| 0.5329 | 12.0 | 84 | 0.6237 | 0.8288 | |
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| 0.5264 | 13.0 | 91 | 0.6135 | 0.8378 | |
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| 0.5264 | 14.0 | 98 | 0.7670 | 0.7568 | |
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| 0.4846 | 15.0 | 105 | 0.6465 | 0.8288 | |
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| 0.4597 | 16.0 | 112 | 0.6354 | 0.8288 | |
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| 0.4597 | 17.0 | 119 | 0.7096 | 0.7838 | |
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| 0.409 | 18.0 | 126 | 0.6364 | 0.8468 | |
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| 0.4321 | 19.0 | 133 | 0.6343 | 0.8108 | |
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| 0.4309 | 20.0 | 140 | 0.5827 | 0.8378 | |
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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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