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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: breastmnist-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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# breastmnist-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: 0.5228 |
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- Accuracy: 0.7308 |
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- Precision: 0.3654 |
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- Recall: 0.5 |
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- F1: 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: 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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| No log | 0.9143 | 8 | 0.8325 | 0.7308 | 0.3654 | 0.5 | 0.4222 | |
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| 0.7315 | 1.9429 | 17 | 0.5744 | 0.7308 | 0.3654 | 0.5 | 0.4222 | |
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| 0.6223 | 2.9714 | 26 | 0.5911 | 0.7308 | 0.3654 | 0.5 | 0.4222 | |
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| 0.5815 | 4.0 | 35 | 0.5743 | 0.7308 | 0.3654 | 0.5 | 0.4222 | |
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| 0.5627 | 4.9143 | 43 | 0.6546 | 0.7308 | 0.3654 | 0.5 | 0.4222 | |
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| 0.5552 | 5.9429 | 52 | 0.5381 | 0.7308 | 0.3654 | 0.5 | 0.4222 | |
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| 0.536 | 6.9714 | 61 | 0.5101 | 0.7949 | 0.8904 | 0.6190 | 0.6308 | |
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| 0.5454 | 8.0 | 70 | 0.5273 | 0.7692 | 0.7246 | 0.6165 | 0.6286 | |
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| 0.5454 | 8.9143 | 78 | 0.5176 | 0.7308 | 0.3654 | 0.5 | 0.4222 | |
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| 0.5058 | 9.1429 | 80 | 0.5228 | 0.7308 | 0.3654 | 0.5 | 0.4222 | |
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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 |
