---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-finetuned-student_kaggle
  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: 1.0
---

<!-- 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-finetuned-student_kaggle

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: 0.0012
- Accuracy: 1.0

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7142        | 1.0   | 47   | 0.6418          | 0.6101   |
| 0.3351        | 2.0   | 94   | 0.2597          | 0.8947   |
| 0.2574        | 3.0   | 141  | 0.1046          | 0.9780   |
| 0.1479        | 4.0   | 188  | 0.0616          | 0.9874   |
| 0.1284        | 5.0   | 235  | 0.0232          | 0.9953   |
| 0.077         | 6.0   | 282  | 0.0150          | 0.9953   |
| 0.103         | 7.0   | 329  | 0.0105          | 0.9984   |
| 0.0922        | 8.0   | 376  | 0.0094          | 0.9984   |
| 0.08          | 9.0   | 423  | 0.0056          | 1.0      |
| 0.0492        | 10.0  | 470  | 0.0045          | 1.0      |
| 0.0574        | 11.0  | 517  | 0.0043          | 1.0      |
| 0.0382        | 12.0  | 564  | 0.0023          | 1.0      |
| 0.0666        | 13.0  | 611  | 0.0022          | 1.0      |
| 0.0477        | 14.0  | 658  | 0.0022          | 1.0      |
| 0.0614        | 15.0  | 705  | 0.0023          | 1.0      |
| 0.0282        | 16.0  | 752  | 0.0014          | 1.0      |
| 0.0659        | 17.0  | 799  | 0.0016          | 1.0      |
| 0.0586        | 18.0  | 846  | 0.0010          | 1.0      |
| 0.0557        | 19.0  | 893  | 0.0013          | 1.0      |
| 0.07          | 20.0  | 940  | 0.0012          | 1.0      |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1