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--- |
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library_name: transformers |
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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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- image-classification |
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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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- f1 |
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- precision |
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- recall |
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model-index: |
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- name: test-trainer |
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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: Chess |
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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: 0.9107142857142857 |
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- name: F1 |
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type: f1 |
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value: 0.9121670865142396 |
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- name: Precision |
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type: precision |
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value: 0.9171626984126985 |
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- name: Recall |
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type: recall |
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value: 0.9107142857142857 |
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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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# test-trainer |
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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 Chess dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7291 |
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- Accuracy: 0.9107 |
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- F1: 0.9122 |
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- Precision: 0.9172 |
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- Recall: 0.9107 |
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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: 2e-05 |
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- train_batch_size: 10 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| No log | 1.0 | 50 | 1.6720 | 0.4821 | 0.4134 | 0.3870 | 0.4821 | |
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| No log | 2.0 | 100 | 1.4652 | 0.6429 | 0.6126 | 0.7414 | 0.6429 | |
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| No log | 3.0 | 150 | 1.1742 | 0.7321 | 0.7210 | 0.7792 | 0.7321 | |
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| No log | 4.0 | 200 | 0.9813 | 0.8393 | 0.8433 | 0.8589 | 0.8393 | |
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| No log | 5.0 | 250 | 0.8312 | 0.8214 | 0.8164 | 0.8516 | 0.8214 | |
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| No log | 6.0 | 300 | 0.7291 | 0.9107 | 0.9122 | 0.9172 | 0.9107 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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