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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: facebook/deit-base-patch16-224 |
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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-deit-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-deit-base-finetuned |
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This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the medmnist-v2 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3440 |
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- Accuracy: 0.8622 |
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- Precision: 0.8623 |
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- Recall: 0.8402 |
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- F1: 0.8487 |
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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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| 0.6158 | 0.9898 | 73 | 0.5674 | 0.7424 | 0.3712 | 0.5 | 0.4261 | |
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| 0.5322 | 1.9932 | 147 | 0.4840 | 0.7729 | 0.8829 | 0.5593 | 0.5396 | |
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| 0.4139 | 2.9966 | 221 | 0.3727 | 0.7939 | 0.8913 | 0.6 | 0.6057 | |
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| 0.3979 | 4.0 | 295 | 0.5270 | 0.7309 | 0.7405 | 0.8139 | 0.7168 | |
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| 0.3858 | 4.9898 | 368 | 0.3062 | 0.8531 | 0.8073 | 0.8623 | 0.8253 | |
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| 0.3704 | 5.9932 | 442 | 0.3774 | 0.8263 | 0.7939 | 0.8734 | 0.8056 | |
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| 0.3345 | 6.9966 | 516 | 0.2403 | 0.9027 | 0.8691 | 0.8812 | 0.8749 | |
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| 0.3875 | 8.0 | 590 | 0.3021 | 0.8817 | 0.8389 | 0.8985 | 0.8590 | |
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| 0.3673 | 8.9898 | 663 | 0.2865 | 0.8969 | 0.8557 | 0.9064 | 0.8749 | |
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| 0.3493 | 9.8983 | 730 | 0.3024 | 0.8740 | 0.8314 | 0.8958 | 0.8515 | |
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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 |
