---
library_name: transformers
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: rsna
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# rsna

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0842
- Accuracy: 0.9697
- Auc: 0.9606
- F1: 0.6931

## 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
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | Auc    | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:------:|
| 0.1066        | 1.0   | 18964 | 0.1029          | 0.9629   | 0.9349 | 0.6084 |
| 0.0872        | 2.0   | 37928 | 0.0921          | 0.9670   | 0.9502 | 0.6681 |
| 0.0900        | 3.0   | 56892 | 0.0872          | 0.9686   | 0.9563 | 0.6803 |
| 0.0902        | 4.0   | 75856 | 0.0847          | 0.9694   | 0.9594 | 0.6934 |
| 0.0824        | 5.0   | 94820 | 0.0842          | 0.9697   | 0.9606 | 0.6931 |


### Framework versions

- Transformers 5.0.0.dev0
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.2