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---
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
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