---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: '100'
  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. -->

# 100

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the cifar100 dataset.
It achieves the following results on the evaluation set:
- Loss: 12.0802
- Accuracy: 0.0094
- Dt Accuracy: 0.0094
- Df Accuracy: 0.0112
- Unlearn Overall Accuracy: 0
- Unlearn Time: None

## 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: 128
- eval_batch_size: 256
- seed: 100
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:|
| No log        | 1.0   | 63   | 1.6527          | 0.6637   | 0                | 0                        | None |
| 0.0           | 2.0   | 126  | 3.9261          | 0.3523   | 0                | 0                        | None |
| 0.0           | 3.0   | 189  | 7.2149          | 0.1325   | 0                | 0                        | None |
| 0.0           | 4.0   | 252  | 9.9746          | 0.0473   | 0                | 0                        | None |
| 0.0           | 5.0   | 315  | 10.5151         | 0.0192   | 0                | 0                        | None |
| 0.0           | 6.0   | 378  | 11.5446         | 0.015    | 0                | 0                        | None |
| 0.0           | 7.0   | 441  | 13.8045         | 0.013    | 0                | 0                        | None |
| 0.0           | 8.0   | 504  | 13.4218         | 0.0107   | 0                | 0                        | None |
| 0.0           | 9.0   | 567  | 12.2747         | 0.0103   | 0                | 0                        | None |
| 0.0           | 10.0  | 630  | 12.0802         | 0.0112   | 0                | 0                        | None |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.19.0
- Tokenizers 0.15.2