---
library_name: transformers
license: apache-2.0
base_model: timm/resnet18.a1_in1k
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: test-timm
  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. -->

# test-timm

This model is a fine-tuned version of [timm/resnet18.a1_in1k](https://huggingface.co/timm/resnet18.a1_in1k) on the davanstrien/zenodo-presentations-open-labels dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5247
- Accuracy: 0.6811

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 1337
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6138        | 1.0   | 180  | 0.6002          | 0.6811   |
| 0.5028        | 2.0   | 360  | 0.5529          | 0.6811   |
| 0.5103        | 3.0   | 540  | 0.5325          | 0.6811   |
| 0.4892        | 4.0   | 720  | 0.5247          | 0.6811   |
| 0.5779        | 5.0   | 900  | 0.5302          | 0.6811   |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.1