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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_fold1 |
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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: 0.4222222222222222 |
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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_fold1 |
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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: 1.3005 |
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- Accuracy: 0.4222 |
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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 | 1.4838 | 0.2222 | |
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| No log | 2.0 | 3 | 1.4436 | 0.2222 | |
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| No log | 2.67 | 4 | 1.4334 | 0.1778 | |
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| No log | 4.0 | 6 | 1.4190 | 0.2667 | |
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| No log | 4.67 | 7 | 1.4121 | 0.2889 | |
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| No log | 6.0 | 9 | 1.3991 | 0.3111 | |
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| 1.3869 | 6.67 | 10 | 1.3926 | 0.3333 | |
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| 1.3869 | 8.0 | 12 | 1.3807 | 0.3556 | |
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| 1.3869 | 8.67 | 13 | 1.3748 | 0.3556 | |
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| 1.3869 | 10.0 | 15 | 1.3643 | 0.3778 | |
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| 1.3869 | 10.67 | 16 | 1.3598 | 0.3778 | |
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| 1.3869 | 12.0 | 18 | 1.3511 | 0.4 | |
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| 1.3869 | 12.67 | 19 | 1.3478 | 0.3778 | |
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| 1.1228 | 14.0 | 21 | 1.3405 | 0.4 | |
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| 1.1228 | 14.67 | 22 | 1.3380 | 0.4 | |
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| 1.1228 | 16.0 | 24 | 1.3323 | 0.4222 | |
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| 1.1228 | 16.67 | 25 | 1.3292 | 0.4222 | |
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| 1.1228 | 18.0 | 27 | 1.3250 | 0.4222 | |
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| 1.1228 | 18.67 | 28 | 1.3231 | 0.4222 | |
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| 0.9505 | 20.0 | 30 | 1.3201 | 0.4222 | |
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| 0.9505 | 20.67 | 31 | 1.3189 | 0.4222 | |
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| 0.9505 | 22.0 | 33 | 1.3162 | 0.4222 | |
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| 0.9505 | 22.67 | 34 | 1.3147 | 0.4222 | |
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| 0.9505 | 24.0 | 36 | 1.3120 | 0.4222 | |
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| 0.9505 | 24.67 | 37 | 1.3113 | 0.4222 | |
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| 0.9505 | 26.0 | 39 | 1.3090 | 0.4222 | |
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| 0.8411 | 26.67 | 40 | 1.3078 | 0.4222 | |
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| 0.8411 | 28.0 | 42 | 1.3057 | 0.4222 | |
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| 0.8411 | 28.67 | 43 | 1.3047 | 0.4222 | |
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| 0.8411 | 30.0 | 45 | 1.3028 | 0.4222 | |
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| 0.8411 | 30.67 | 46 | 1.3020 | 0.4222 | |
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| 0.8411 | 32.0 | 48 | 1.3010 | 0.4222 | |
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| 0.8411 | 32.67 | 49 | 1.3007 | 0.4222 | |
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| 0.7881 | 33.33 | 50 | 1.3005 | 0.4222 | |
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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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