---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-50-bottomCleanedData
  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: 0.8342792281498297
---

<!-- 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-bottomCleanedData

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: 0.4809
- Accuracy: 0.8343

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 7
- total_train_batch_size: 56
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.01
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.3235        | 1.0   | 141  | 1.3266          | 0.5096   |
| 1.1546        | 2.0   | 283  | 1.1380          | 0.5153   |
| 0.9412        | 2.99  | 424  | 0.8690          | 0.6515   |
| 0.8539        | 4.0   | 566  | 0.6672          | 0.7594   |
| 0.7967        | 4.99  | 707  | 0.6256          | 0.7503   |
| 0.7679        | 6.0   | 849  | 0.5357          | 0.8229   |
| 0.7265        | 7.0   | 991  | 0.5698          | 0.7832   |
| 0.7395        | 8.0   | 1132 | 0.5125          | 0.8161   |
| 0.7029        | 9.0   | 1274 | 0.4993          | 0.8150   |
| 0.7275        | 9.96  | 1410 | 0.4809          | 0.8343   |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3