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--- |
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license: apache-2.0 |
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base_model: facebook/deit-tiny-patch16-224 |
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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: hushem_1x_deit_tiny_adamax_lr00001_fold5 |
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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: 0.4634146341463415 |
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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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# hushem_1x_deit_tiny_adamax_lr00001_fold5 |
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This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2718 |
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- Accuracy: 0.4634 |
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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: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 50 |
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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 | 0.67 | 1 | 1.6411 | 0.1220 | |
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| No log | 2.0 | 3 | 1.5318 | 0.1951 | |
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| No log | 2.67 | 4 | 1.5063 | 0.1707 | |
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| No log | 4.0 | 6 | 1.4764 | 0.3171 | |
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| No log | 4.67 | 7 | 1.4625 | 0.3171 | |
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| No log | 6.0 | 9 | 1.4352 | 0.3902 | |
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| 1.379 | 6.67 | 10 | 1.4210 | 0.4390 | |
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| 1.379 | 8.0 | 12 | 1.3993 | 0.4390 | |
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| 1.379 | 8.67 | 13 | 1.3906 | 0.4390 | |
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| 1.379 | 10.0 | 15 | 1.3747 | 0.4146 | |
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| 1.379 | 10.67 | 16 | 1.3676 | 0.4146 | |
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| 1.379 | 12.0 | 18 | 1.3554 | 0.4146 | |
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| 1.379 | 12.67 | 19 | 1.3500 | 0.4146 | |
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| 1.107 | 14.0 | 21 | 1.3389 | 0.4146 | |
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| 1.107 | 14.67 | 22 | 1.3348 | 0.4146 | |
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| 1.107 | 16.0 | 24 | 1.3265 | 0.4390 | |
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| 1.107 | 16.67 | 25 | 1.3236 | 0.4634 | |
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| 1.107 | 18.0 | 27 | 1.3162 | 0.4634 | |
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| 1.107 | 18.67 | 28 | 1.3129 | 0.4390 | |
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| 0.9495 | 20.0 | 30 | 1.3051 | 0.4390 | |
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| 0.9495 | 20.67 | 31 | 1.3019 | 0.4390 | |
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| 0.9495 | 22.0 | 33 | 1.2961 | 0.4390 | |
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| 0.9495 | 22.67 | 34 | 1.2934 | 0.4634 | |
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| 0.9495 | 24.0 | 36 | 1.2879 | 0.4390 | |
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| 0.9495 | 24.67 | 37 | 1.2851 | 0.4390 | |
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| 0.9495 | 26.0 | 39 | 1.2815 | 0.4390 | |
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| 0.8401 | 26.67 | 40 | 1.2802 | 0.4390 | |
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| 0.8401 | 28.0 | 42 | 1.2775 | 0.4390 | |
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| 0.8401 | 28.67 | 43 | 1.2761 | 0.4390 | |
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| 0.8401 | 30.0 | 45 | 1.2740 | 0.4390 | |
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| 0.8401 | 30.67 | 46 | 1.2734 | 0.4390 | |
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| 0.8401 | 32.0 | 48 | 1.2723 | 0.4634 | |
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| 0.8401 | 32.67 | 49 | 1.2719 | 0.4634 | |
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| 0.7816 | 33.33 | 50 | 1.2718 | 0.4634 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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