---
license: apache-2.0
base_model: microsoft/resnet-18
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet-18-resnet-18
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: train
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.3541666666666667
---

<!-- 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-18-resnet-18

This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 5878685290980833992550249398272.0000
- Accuracy: 0.3542

## 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 |
|:------------------------------------:|:------:|:----:|:------------------------------------:|:--------:|
| No log                               | 0.8889 | 6    | 5256596847186447919144532705280.0000 | 0.3542   |
| 6252348666680642391375611953152.0000 | 1.9259 | 13   | 5816409290772115792559022800896.0000 | 0.3542   |
| 5941338476045271956843984322560.0000 | 2.9630 | 20   | 5569209952566045840858865991680.0000 | 0.3542   |
| 5941338476045271956843984322560.0000 | 4.0    | 27   | 5764530657074993210784856670208.0000 | 0.3542   |
| 5978113032337293509815187800064.0000 | 4.8889 | 33   | 5717174614869048956753266343936.0000 | 0.3542   |
| 6377920275134342219963975073792.0000 | 5.9259 | 40   | 5885479454087068208512098107392.0000 | 0.3542   |
| 6377920275134342219963975073792.0000 | 6.9630 | 47   | 5693683372805207289944963284992.0000 | 0.3542   |
| 6201930657158778429750307192832.0000 | 8.0    | 54   | 5815479022353922335409086398464.0000 | 0.3542   |
| 6266525497982100125501481811968.0000 | 8.8889 | 60   | 5878685290980833992550249398272.0000 | 0.3542   |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1