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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_lr0001_fold4 |
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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: 0.8333333333333334 |
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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_lr0001_fold4 |
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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: 0.5599 |
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- Accuracy: 0.8333 |
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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: 0.0001 |
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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 | 1.6749 | 0.3095 | |
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| No log | 2.0 | 3 | 1.3545 | 0.3333 | |
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| No log | 2.67 | 4 | 1.3451 | 0.2857 | |
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| No log | 4.0 | 6 | 1.2535 | 0.5238 | |
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| No log | 4.67 | 7 | 1.2290 | 0.4286 | |
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| No log | 6.0 | 9 | 1.1555 | 0.5 | |
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| 1.2457 | 6.67 | 10 | 1.0938 | 0.5 | |
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| 1.2457 | 8.0 | 12 | 0.9608 | 0.4762 | |
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| 1.2457 | 8.67 | 13 | 0.8825 | 0.5952 | |
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| 1.2457 | 10.0 | 15 | 0.7678 | 0.7143 | |
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| 1.2457 | 10.67 | 16 | 0.7184 | 0.7857 | |
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| 1.2457 | 12.0 | 18 | 0.6658 | 0.7619 | |
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| 1.2457 | 12.67 | 19 | 0.6361 | 0.7619 | |
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| 0.4167 | 14.0 | 21 | 0.6247 | 0.8095 | |
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| 0.4167 | 14.67 | 22 | 0.6111 | 0.7857 | |
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| 0.4167 | 16.0 | 24 | 0.5896 | 0.7857 | |
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| 0.4167 | 16.67 | 25 | 0.5886 | 0.7381 | |
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| 0.4167 | 18.0 | 27 | 0.6107 | 0.7619 | |
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| 0.4167 | 18.67 | 28 | 0.6198 | 0.7619 | |
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| 0.0627 | 20.0 | 30 | 0.6194 | 0.7619 | |
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| 0.0627 | 20.67 | 31 | 0.6092 | 0.7619 | |
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| 0.0627 | 22.0 | 33 | 0.5917 | 0.7857 | |
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| 0.0627 | 22.67 | 34 | 0.5871 | 0.7857 | |
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| 0.0627 | 24.0 | 36 | 0.5872 | 0.8095 | |
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| 0.0627 | 24.67 | 37 | 0.5896 | 0.8095 | |
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| 0.0627 | 26.0 | 39 | 0.5921 | 0.8095 | |
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| 0.0081 | 26.67 | 40 | 0.5908 | 0.8095 | |
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| 0.0081 | 28.0 | 42 | 0.5818 | 0.8095 | |
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| 0.0081 | 28.67 | 43 | 0.5772 | 0.8095 | |
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| 0.0081 | 30.0 | 45 | 0.5685 | 0.8095 | |
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| 0.0081 | 30.67 | 46 | 0.5654 | 0.8095 | |
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| 0.0081 | 32.0 | 48 | 0.5614 | 0.8333 | |
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| 0.0081 | 32.67 | 49 | 0.5603 | 0.8333 | |
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| 0.0038 | 33.33 | 50 | 0.5599 | 0.8333 | |
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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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