---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: freeway_resnet50_Model
  results: []
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/huangyangyu/huggingface/runs/zbrisuho)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/huangyangyu/huggingface/runs/zbrisuho)
# freeway_resnet50_Model

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0047
- 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: 2e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.3403        | 0.4808  | 100  | 0.3006          | 0.9454   |
| 0.3093        | 0.9615  | 200  | 0.2498          | 0.9540   |
| 0.2743        | 1.4423  | 300  | 0.2004          | 0.9666   |
| 0.2375        | 1.9231  | 400  | 0.1552          | 0.9798   |
| 0.2118        | 2.4038  | 500  | 0.1143          | 0.9852   |
| 0.1953        | 2.8846  | 600  | 0.1095          | 0.9844   |
| 0.1807        | 3.3654  | 700  | 0.0893          | 0.9895   |
| 0.1623        | 3.8462  | 800  | 0.0682          | 0.9914   |
| 0.1414        | 4.3269  | 900  | 0.0560          | 0.9941   |
| 0.1296        | 4.8077  | 1000 | 0.0511          | 0.9933   |
| 0.1195        | 5.2885  | 1100 | 0.0344          | 0.9957   |
| 0.1114        | 5.7692  | 1200 | 0.0303          | 0.9984   |
| 0.1034        | 6.25    | 1300 | 0.0298          | 0.9965   |
| 0.0994        | 6.7308  | 1400 | 0.0257          | 0.9987   |
| 0.0907        | 7.2115  | 1500 | 0.0225          | 0.9992   |
| 0.0881        | 7.6923  | 1600 | 0.0201          | 0.9987   |
| 0.0801        | 8.1731  | 1700 | 0.0157          | 1.0      |
| 0.0764        | 8.6538  | 1800 | 0.0141          | 0.9995   |
| 0.0746        | 9.1346  | 1900 | 0.0142          | 0.9995   |
| 0.0715        | 9.6154  | 2000 | 0.0115          | 0.9995   |
| 0.074         | 10.0962 | 2100 | 0.0124          | 0.9992   |
| 0.0677        | 10.5769 | 2200 | 0.0102          | 0.9995   |
| 0.0679        | 11.0577 | 2300 | 0.0101          | 0.9995   |
| 0.068         | 11.5385 | 2400 | 0.0110          | 0.9992   |
| 0.0589        | 12.0192 | 2500 | 0.0081          | 0.9997   |
| 0.0581        | 12.5    | 2600 | 0.0090          | 0.9995   |
| 0.058         | 12.9808 | 2700 | 0.0080          | 0.9995   |
| 0.0559        | 13.4615 | 2800 | 0.0082          | 0.9997   |
| 0.0547        | 13.9423 | 2900 | 0.0062          | 1.0      |
| 0.0493        | 14.4231 | 3000 | 0.0061          | 1.0      |
| 0.0506        | 14.9038 | 3100 | 0.0054          | 1.0      |
| 0.0466        | 15.3846 | 3200 | 0.0068          | 0.9995   |
| 0.0506        | 15.8654 | 3300 | 0.0055          | 1.0      |
| 0.0481        | 16.3462 | 3400 | 0.0053          | 1.0      |
| 0.0523        | 16.8269 | 3500 | 0.0053          | 1.0      |
| 0.0537        | 17.3077 | 3600 | 0.0061          | 0.9995   |
| 0.0474        | 17.7885 | 3700 | 0.0049          | 1.0      |
| 0.0511        | 18.2692 | 3800 | 0.0054          | 1.0      |
| 0.0474        | 18.75   | 3900 | 0.0052          | 1.0      |
| 0.0456        | 19.2308 | 4000 | 0.0062          | 0.9997   |
| 0.0385        | 19.7115 | 4100 | 0.0047          | 1.0      |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.1.1
- Datasets 2.19.2
- Tokenizers 0.19.1