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---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- image-classification
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: camera-type
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: validation
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.9382716049382716
---
<!-- 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. -->
# camera-type
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: 0.1654
- Accuracy: 0.9383
## 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: 0.0001
- train_batch_size: 10
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.4597 | 0.5 | 200 | 0.2801 | 0.9242 |
| 0.1375 | 0.99 | 400 | 0.1654 | 0.9383 |
| 0.0795 | 1.49 | 600 | 0.1904 | 0.9383 |
| 0.0686 | 1.98 | 800 | 0.1810 | 0.9453 |
| 0.026 | 2.48 | 1000 | 0.2216 | 0.9400 |
| 0.0495 | 2.97 | 1200 | 0.2096 | 0.9453 |
| 0.0487 | 3.47 | 1400 | 0.2174 | 0.9436 |
| 0.0268 | 3.96 | 1600 | 0.2304 | 0.9453 |
| 0.0254 | 4.46 | 1800 | 0.2574 | 0.9400 |
| 0.0186 | 4.95 | 2000 | 0.3212 | 0.9383 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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