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--- |
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license: apache-2.0 |
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library_name: peft |
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tags: |
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- generated_from_trainer |
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base_model: microsoft/beit-base-patch16-224-pt22k-ft22k |
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datasets: |
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- medmnist-v2 |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: pneumoniamnist-beit-base-finetuned |
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results: [] |
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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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# pneumoniamnist-beit-base-finetuned |
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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 medmnist-v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3960 |
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- Accuracy: 0.8446 |
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- Precision: 0.8354 |
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- Recall: 0.8312 |
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- F1: 0.8332 |
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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: 0.005 |
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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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- num_epochs: 10 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.5947 | 0.9898 | 73 | 0.5165 | 0.7424 | 0.3712 | 0.5 | 0.4261 | |
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| 0.4888 | 1.9932 | 147 | 0.3450 | 0.8569 | 0.8116 | 0.8190 | 0.8151 | |
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| 0.4022 | 2.9966 | 221 | 0.4225 | 0.8340 | 0.7914 | 0.8567 | 0.8079 | |
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| 0.4319 | 4.0 | 295 | 0.3600 | 0.8588 | 0.8123 | 0.8589 | 0.8292 | |
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| 0.3836 | 4.9898 | 368 | 0.3665 | 0.8511 | 0.8054 | 0.8610 | 0.8233 | |
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| 0.3887 | 5.9932 | 442 | 0.3667 | 0.8645 | 0.8197 | 0.8749 | 0.8383 | |
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| 0.3947 | 6.9966 | 516 | 0.3951 | 0.8531 | 0.8098 | 0.8744 | 0.8283 | |
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| 0.3741 | 8.0 | 590 | 0.3449 | 0.8683 | 0.8229 | 0.8678 | 0.8398 | |
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| 0.3964 | 8.9898 | 663 | 0.3625 | 0.8588 | 0.8128 | 0.8638 | 0.8305 | |
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| 0.3845 | 9.8983 | 730 | 0.3569 | 0.8569 | 0.8111 | 0.8649 | 0.8292 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
