
<!-- 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-101-CivilEng11k_3Classes-new

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:
- eval_loss: 0.0001
- eval_accuracy: 1.0
- eval_runtime: 58.9592
- eval_samples_per_second: 10.007
- eval_steps_per_second: 0.322
- epoch: 5.0
- step: 140

## 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: 0.0005
- 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

### Framework versions

- Transformers 4.37.2
- Pytorch 2.0.1+cpu
- Datasets 2.18.0
- Tokenizers 0.15.1

crazing live_knot steel_defect