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--- |
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license: apache-2.0 |
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base_model: microsoft/beit-base-patch16-224-pt22k-ft22k |
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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_40x_beit_base_f5 |
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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: 0.9512195121951219 |
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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_40x_beit_base_f5 |
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2681 |
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- Accuracy: 0.9512 |
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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: 10 |
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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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| 0.0802 | 1.0 | 110 | 0.6945 | 0.8049 | |
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| 0.028 | 2.0 | 220 | 0.5751 | 0.9024 | |
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| 0.002 | 3.0 | 330 | 0.3641 | 0.9268 | |
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| 0.0009 | 4.0 | 440 | 0.5616 | 0.8780 | |
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| 0.0004 | 5.0 | 550 | 0.2822 | 0.9024 | |
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| 0.0003 | 6.0 | 660 | 0.7387 | 0.8537 | |
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| 0.0018 | 7.0 | 770 | 0.1999 | 0.9512 | |
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| 0.0001 | 8.0 | 880 | 0.3046 | 0.9512 | |
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| 0.0011 | 9.0 | 990 | 0.2897 | 0.9268 | |
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| 0.0002 | 10.0 | 1100 | 0.2681 | 0.9512 | |
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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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