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--- |
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license: apache-2.0 |
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base_model: microsoft/beit-base-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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- precision |
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- recall |
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model-index: |
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- name: beit-base-patch16-224 |
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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: validation |
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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: 0.85 |
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- name: Precision |
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type: precision |
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value: 0.8455590062111802 |
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- name: Recall |
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type: recall |
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value: 0.85 |
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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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# beit-base-patch16-224 |
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4871 |
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- Accuracy: 0.85 |
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- Precision: 0.8456 |
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- Recall: 0.85 |
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- F1 Score: 0.8464 |
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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: 4 |
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- total_train_batch_size: 256 |
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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: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 Score | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:| |
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| No log | 1.0 | 4 | 0.5784 | 0.7333 | 0.5378 | 0.7333 | 0.6205 | |
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| No log | 2.0 | 8 | 0.5813 | 0.7375 | 0.7030 | 0.7375 | 0.6441 | |
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| No log | 3.0 | 12 | 0.5486 | 0.7417 | 0.7297 | 0.7417 | 0.7343 | |
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| No log | 4.0 | 16 | 0.5394 | 0.7542 | 0.7333 | 0.7542 | 0.7370 | |
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| No log | 5.0 | 20 | 0.5067 | 0.775 | 0.7658 | 0.775 | 0.7321 | |
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| No log | 6.0 | 24 | 0.5542 | 0.7958 | 0.7966 | 0.7958 | 0.7613 | |
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| No log | 7.0 | 28 | 0.4753 | 0.7958 | 0.7834 | 0.7958 | 0.7758 | |
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| 0.5325 | 8.0 | 32 | 0.5265 | 0.7792 | 0.7661 | 0.7792 | 0.7448 | |
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| 0.5325 | 9.0 | 36 | 0.4789 | 0.8208 | 0.8134 | 0.8208 | 0.8067 | |
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| 0.5325 | 10.0 | 40 | 0.4939 | 0.7875 | 0.7932 | 0.7875 | 0.7900 | |
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| 0.5325 | 11.0 | 44 | 0.4917 | 0.8042 | 0.8032 | 0.8042 | 0.8037 | |
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| 0.5325 | 12.0 | 48 | 0.5001 | 0.8083 | 0.8019 | 0.8083 | 0.8041 | |
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| 0.5325 | 13.0 | 52 | 0.4742 | 0.8 | 0.7897 | 0.8 | 0.7915 | |
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| 0.5325 | 14.0 | 56 | 0.5439 | 0.7875 | 0.8037 | 0.7875 | 0.7932 | |
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| 0.3381 | 15.0 | 60 | 0.5436 | 0.8333 | 0.8265 | 0.8333 | 0.8263 | |
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| 0.3381 | 16.0 | 64 | 0.4989 | 0.8375 | 0.8312 | 0.8375 | 0.8288 | |
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| 0.3381 | 17.0 | 68 | 0.4949 | 0.8333 | 0.8282 | 0.8333 | 0.8296 | |
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| 0.3381 | 18.0 | 72 | 0.4709 | 0.8292 | 0.8283 | 0.8292 | 0.8287 | |
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| 0.3381 | 19.0 | 76 | 0.4680 | 0.8167 | 0.8133 | 0.8167 | 0.8147 | |
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| 0.3381 | 20.0 | 80 | 0.5053 | 0.8417 | 0.8362 | 0.8417 | 0.8371 | |
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| 0.3381 | 21.0 | 84 | 0.5480 | 0.8458 | 0.8459 | 0.8458 | 0.8322 | |
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| 0.3381 | 22.0 | 88 | 0.4548 | 0.8542 | 0.8512 | 0.8542 | 0.8522 | |
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| 0.2076 | 23.0 | 92 | 0.4891 | 0.8458 | 0.8407 | 0.8458 | 0.8376 | |
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| 0.2076 | 24.0 | 96 | 0.4981 | 0.85 | 0.8486 | 0.85 | 0.8492 | |
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| 0.2076 | 25.0 | 100 | 0.4993 | 0.8458 | 0.8426 | 0.8458 | 0.8438 | |
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| 0.2076 | 26.0 | 104 | 0.5026 | 0.8542 | 0.8503 | 0.8542 | 0.8514 | |
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| 0.2076 | 27.0 | 108 | 0.4944 | 0.8542 | 0.8522 | 0.8542 | 0.8530 | |
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| 0.2076 | 28.0 | 112 | 0.4821 | 0.8542 | 0.8549 | 0.8542 | 0.8545 | |
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| 0.2076 | 29.0 | 116 | 0.4714 | 0.8583 | 0.8559 | 0.8583 | 0.8568 | |
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| 0.138 | 30.0 | 120 | 0.4705 | 0.8583 | 0.8559 | 0.8583 | 0.8568 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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