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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: ArtiSikhwal/headlight_11_12_2024_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: headlight_12_12_2024_google_vit-base-patch16-224-in21k |
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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: test |
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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: 0.9014772078868953 |
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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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# headlight_12_12_2024_google_vit-base-patch16-224-in21k |
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This model is a fine-tuned version of [ArtiSikhwal/headlight_11_12_2024_google_vit-base-patch16-224-in21k](https://huggingface.co/ArtiSikhwal/headlight_11_12_2024_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: 0.2587 |
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- Accuracy: 0.9015 |
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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: 8 |
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- total_train_batch_size: 512 |
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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: 6 |
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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 | 0.9995 | 492 | 0.2682 | 0.8973 | |
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| 0.1998 | 1.9990 | 984 | 0.2701 | 0.8982 | |
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| 0.1988 | 2.9985 | 1476 | 0.2708 | 0.8974 | |
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| 0.1976 | 4.0 | 1969 | 0.2609 | 0.9013 | |
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| 0.2131 | 4.9995 | 2461 | 0.2584 | 0.9011 | |
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| 0.2169 | 5.9970 | 2952 | 0.2587 | 0.9015 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.4.0 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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