---
library_name: transformers
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: cat_dog_classifier
  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. -->

# cat_dog_classifier

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: 0.0884
- Accuracy: 0.9688

## 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: 5e-05
- train_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 293  | 0.1872          | 0.9440   |
| 0.3326        | 2.0   | 586  | 0.1120          | 0.9590   |
| 0.3326        | 3.0   | 879  | 0.0877          | 0.9677   |
| 0.1182        | 4.0   | 1172 | 0.0940          | 0.9641   |
| 0.1182        | 5.0   | 1465 | 0.0884          | 0.9688   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.2.0
- Tokenizers 0.19.1