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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 |
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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 |
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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: 0.5284 |
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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 | 1.0120 | 0.7 | |
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| No log | 2.0 | 4 | 0.9958 | 0.8 | |
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| No log | 3.0 | 6 | 0.9576 | 0.8333 | |
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| No log | 4.0 | 8 | 0.8673 | 0.8333 | |
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| 0.8292 | 5.0 | 10 | 0.8140 | 0.8667 | |
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| 0.8292 | 6.0 | 12 | 0.7034 | 0.9 | |
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| 0.8292 | 7.0 | 14 | 0.7036 | 0.9 | |
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| 0.8292 | 8.0 | 16 | 0.6949 | 0.9333 | |
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| 0.8292 | 9.0 | 18 | 0.5620 | 0.9667 | |
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| 0.6112 | 10.0 | 20 | 0.5829 | 0.9333 | |
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| 0.6112 | 11.0 | 22 | 0.6530 | 0.9 | |
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| 0.6112 | 12.0 | 24 | 0.5664 | 0.9333 | |
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| 0.6112 | 13.0 | 26 | 0.5084 | 1.0 | |
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| 0.6112 | 14.0 | 28 | 0.6490 | 0.8333 | |
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| 0.4805 | 15.0 | 30 | 0.4700 | 1.0 | |
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| 0.4805 | 16.0 | 32 | 0.5473 | 0.9333 | |
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| 0.4805 | 17.0 | 34 | 0.4928 | 0.9667 | |
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| 0.4805 | 18.0 | 36 | 0.5023 | 0.9667 | |
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| 0.4805 | 19.0 | 38 | 0.4885 | 0.9333 | |
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| 0.4145 | 20.0 | 40 | 0.5284 | 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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