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

# resnet_aug

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: 1.2587
- Accuracy: 0.4686

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- 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

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6578        | 1.0   | 240  | 1.6593          | 0.2533   |
| 1.5544        | 2.0   | 480  | 1.5545          | 0.2803   |
| 1.4653        | 3.0   | 720  | 1.4689          | 0.3404   |
| 1.3595        | 4.0   | 960  | 1.3931          | 0.3914   |
| 1.2991        | 5.0   | 1200 | 1.3410          | 0.4208   |
| 1.2512        | 6.0   | 1440 | 1.3049          | 0.4421   |
| 1.1948        | 7.0   | 1680 | 1.2843          | 0.4552   |
| 1.1679        | 8.0   | 1920 | 1.2667          | 0.4613   |
| 1.1842        | 9.0   | 2160 | 1.2635          | 0.4668   |
| 1.1268        | 10.0  | 2400 | 1.2587          | 0.4686   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Tokenizers 0.19.1