---
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: 0.4889937106918239
---

<!-- 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: 34897389209777069883392.0000
- Accuracy: 0.4890

## 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: 5

### Training results

| Training Loss                | Epoch  | Step | Validation Loss              | Accuracy |
|:----------------------------:|:------:|:----:|:----------------------------:|:--------:|
| 33718936798882659565568.0000 | 0.9362 | 11   | 34897389209777069883392.0000 | 0.4890   |
| 32438469749948979085312.0000 | 1.9574 | 23   | 34897389209777069883392.0000 | 0.4890   |
| 33363246103192638849024.0000 | 2.9787 | 35   | 34897389209777069883392.0000 | 0.4890   |
| 32954207567756639862784.0000 | 4.0    | 47   | 34897389209777069883392.0000 | 0.4890   |
| 32794156842759294550016.0000 | 4.6809 | 55   | 34897389209777069883392.0000 | 0.4890   |


### Framework versions

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