---
license: apache-2.0
base_model: microsoft/resnet-101
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-101-CivilEng11k_3Classes
  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
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# resnet-101-CivilEng11k_3Classes

This model is a fine-tuned version of [microsoft/resnet-101](https://huggingface.co/microsoft/resnet-101) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0587
- 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: 0.0002
- 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0885        | 1.0   | 37   | 0.8955          | 0.4305   |
| 0.6832        | 2.0   | 74   | 0.4990          | 0.8475   |
| 0.2591        | 3.0   | 111  | 0.0587          | 1.0      |
| 0.024         | 4.0   | 148  | 0.0026          | 1.0      |
| 0.005         | 5.0   | 185  | 0.0007          | 1.0      |
| 0.0121        | 6.0   | 222  | 0.0005          | 1.0      |
| 0.0214        | 7.0   | 259  | 0.0003          | 1.0      |
| 0.0035        | 8.0   | 296  | 0.0002          | 1.0      |
| 0.0026        | 9.0   | 333  | 0.0002          | 1.0      |
| 0.0054        | 10.0  | 370  | 0.0002          | 1.0      |


### Framework versions

- Transformers 4.37.2
- Pytorch 1.12.1
- Datasets 2.18.0
- Tokenizers 0.15.1