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---
license: apache-2.0
base_model: microsoft/swin-tiny-patch4-window7-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: swin-tiny-patch4-window7-224-finetuned-RCC
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# swin-tiny-patch4-window7-224-finetuned-RCC
This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3526
- Accuracy: 0.8226
- Precision: 0.9245
- Recall: 0.875
- F1: 0.5829
- Auc: 0.6042
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| No log | 1.0 | 7 | 0.3296 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 |
| 0.4795 | 2.0 | 14 | 0.3129 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 |
| 0.2503 | 3.0 | 21 | 0.3182 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 |
| 0.2503 | 4.0 | 28 | 0.2973 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 |
| 0.2231 | 5.0 | 35 | 0.3275 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 |
| 0.1791 | 6.0 | 42 | 0.3147 | 0.9032 | 0.9032 | 1.0 | 0.4746 | 0.5 |
| 0.1791 | 7.0 | 49 | 0.3401 | 0.8978 | 0.9071 | 0.9881 | 0.5206 | 0.5218 |
| 0.1361 | 8.0 | 56 | 0.3885 | 0.7849 | 0.9211 | 0.8333 | 0.5529 | 0.5833 |
| 0.1245 | 9.0 | 63 | 0.3192 | 0.8817 | 0.9195 | 0.9524 | 0.6012 | 0.5873 |
| 0.0902 | 10.0 | 70 | 0.3526 | 0.8226 | 0.9245 | 0.875 | 0.5829 | 0.6042 |
### Framework versions
- Transformers 4.41.1
- Pytorch 2.0.0+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1
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