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---
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license: apache-2.0
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base_model: microsoft/resnet-50
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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model-index:
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- name: freeway_resnet50_Model
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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[<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)
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[<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)
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# freeway_resnet50_Model
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0047
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- Accuracy: 1.0
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 20
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-------:|:----:|:---------------:|:--------:|
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| 0.3403 | 0.4808 | 100 | 0.3006 | 0.9454 |
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| 0.3093 | 0.9615 | 200 | 0.2498 | 0.9540 |
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| 0.2743 | 1.4423 | 300 | 0.2004 | 0.9666 |
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| 0.2375 | 1.9231 | 400 | 0.1552 | 0.9798 |
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| 0.2118 | 2.4038 | 500 | 0.1143 | 0.9852 |
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| 0.1953 | 2.8846 | 600 | 0.1095 | 0.9844 |
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| 0.1807 | 3.3654 | 700 | 0.0893 | 0.9895 |
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| 0.1623 | 3.8462 | 800 | 0.0682 | 0.9914 |
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| 0.1414 | 4.3269 | 900 | 0.0560 | 0.9941 |
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| 0.1296 | 4.8077 | 1000 | 0.0511 | 0.9933 |
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| 0.1195 | 5.2885 | 1100 | 0.0344 | 0.9957 |
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| 0.1114 | 5.7692 | 1200 | 0.0303 | 0.9984 |
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| 0.1034 | 6.25 | 1300 | 0.0298 | 0.9965 |
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| 0.0994 | 6.7308 | 1400 | 0.0257 | 0.9987 |
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| 0.0907 | 7.2115 | 1500 | 0.0225 | 0.9992 |
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| 0.0881 | 7.6923 | 1600 | 0.0201 | 0.9987 |
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| 0.0801 | 8.1731 | 1700 | 0.0157 | 1.0 |
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| 0.0764 | 8.6538 | 1800 | 0.0141 | 0.9995 |
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| 0.0746 | 9.1346 | 1900 | 0.0142 | 0.9995 |
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| 0.0715 | 9.6154 | 2000 | 0.0115 | 0.9995 |
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| 0.074 | 10.0962 | 2100 | 0.0124 | 0.9992 |
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| 0.0677 | 10.5769 | 2200 | 0.0102 | 0.9995 |
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| 0.0679 | 11.0577 | 2300 | 0.0101 | 0.9995 |
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| 0.068 | 11.5385 | 2400 | 0.0110 | 0.9992 |
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| 0.0589 | 12.0192 | 2500 | 0.0081 | 0.9997 |
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| 0.0581 | 12.5 | 2600 | 0.0090 | 0.9995 |
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| 0.058 | 12.9808 | 2700 | 0.0080 | 0.9995 |
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| 0.0559 | 13.4615 | 2800 | 0.0082 | 0.9997 |
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| 0.0547 | 13.9423 | 2900 | 0.0062 | 1.0 |
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| 0.0493 | 14.4231 | 3000 | 0.0061 | 1.0 |
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| 0.0506 | 14.9038 | 3100 | 0.0054 | 1.0 |
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| 0.0466 | 15.3846 | 3200 | 0.0068 | 0.9995 |
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| 0.0506 | 15.8654 | 3300 | 0.0055 | 1.0 |
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| 0.0481 | 16.3462 | 3400 | 0.0053 | 1.0 |
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| 0.0523 | 16.8269 | 3500 | 0.0053 | 1.0 |
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| 0.0537 | 17.3077 | 3600 | 0.0061 | 0.9995 |
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| 0.0474 | 17.7885 | 3700 | 0.0049 | 1.0 |
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| 0.0511 | 18.2692 | 3800 | 0.0054 | 1.0 |
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| 0.0474 | 18.75 | 3900 | 0.0052 | 1.0 |
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| 0.0456 | 19.2308 | 4000 | 0.0062 | 0.9997 |
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| 0.0385 | 19.7115 | 4100 | 0.0047 | 1.0 |
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### Framework versions
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- Transformers 4.42.0.dev0
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- Pytorch 2.1.1
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- Datasets 2.19.2
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- Tokenizers 0.19.1
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