---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-drfx-CT-classifier
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.7647058823529411
---

<!-- 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. -->

# resnet-50-drfx-CT-classifier

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6761
- Accuracy: 0.7647

## 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: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 4    | 0.6965          | 0.2941   |
| No log        | 2.0   | 8    | 0.6920          | 0.4706   |
| 0.6857        | 3.0   | 12   | 0.7012          | 0.2941   |
| 0.6857        | 4.0   | 16   | 0.6919          | 0.5882   |
| 0.6896        | 5.0   | 20   | 0.6761          | 0.7647   |
| 0.6896        | 6.0   | 24   | 0.6855          | 0.6471   |
| 0.6896        | 7.0   | 28   | 0.6757          | 0.7059   |
| 0.6936        | 8.0   | 32   | 0.6810          | 0.5294   |
| 0.6936        | 9.0   | 36   | 0.6744          | 0.7059   |
| 0.6827        | 10.0  | 40   | 0.6796          | 0.6471   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3