---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: '42'
  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. -->

# 42

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: -61.2603
- Accuracy: 0.0145
- Dt Accuracy: 0.0145
- Df Accuracy: 0.0132
- 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: 5e-05
- train_batch_size: 128
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:|
| No log        | 1.0   | 40   | -0.6705         | 0.8614   | 0.2576           | 0.2576                   | None |
| No log        | 2.0   | 80   | -1.1856         | 0.7334   | 0.4182           | 0.4182                   | None |
| No log        | 3.0   | 120  | -3.0241         | 0.4682   | 0                | 0                        | None |
| No log        | 4.0   | 160  | -6.8932         | 0.2358   | 0                | 0                        | None |
| No log        | 5.0   | 200  | -11.5720        | 0.1004   | 0                | 0                        | None |
| No log        | 6.0   | 240  | -16.6897        | 0.0524   | 0                | 0                        | None |
| No log        | 7.0   | 280  | -21.7166        | 0.035    | 0                | 0                        | None |
| No log        | 8.0   | 320  | -26.8608        | 0.0274   | 0                | 0                        | None |
| No log        | 9.0   | 360  | -31.0666        | 0.0212   | 0                | 0                        | None |
| No log        | 10.0  | 400  | -38.7816        | 0.0186   | 0                | 0                        | None |
| No log        | 11.0  | 440  | -41.5065        | 0.017    | 0                | 0                        | None |
| No log        | 12.0  | 480  | -45.3635        | 0.017    | 0                | 0                        | None |
| -18.2648      | 13.0  | 520  | -49.5281        | 0.016    | 0                | 0                        | None |
| -18.2648      | 14.0  | 560  | -53.6067        | 0.0154   | 0                | 0                        | None |
| -18.2648      | 15.0  | 600  | -50.5046        | 0.0158   | 0                | 0                        | None |
| -18.2648      | 16.0  | 640  | -55.5001        | 0.0148   | 0                | 0                        | None |
| -18.2648      | 17.0  | 680  | -55.9571        | 0.0148   | 0                | 0                        | None |
| -18.2648      | 18.0  | 720  | -53.0937        | 0.015    | 0                | 0                        | None |
| -18.2648      | 19.0  | 760  | -54.5232        | 0.0144   | 0                | 0                        | None |
| -18.2648      | 20.0  | 800  | -61.2603        | 0.0132   | 0                | 0                        | None |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2