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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: vit-base-beans
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. -->
# vit-base-beans
This model is a fine-tuned version of [timm/resnet18.a1_in1k](https://huggingface.co/timm/resnet18.a1_in1k) on the beans dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0324
- Accuracy: 0.6917
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0884 | 1.0 | 130 | 1.0903 | 0.4060 |
| 1.0721 | 2.0 | 260 | 1.0681 | 0.5188 |
| 1.0623 | 3.0 | 390 | 1.0460 | 0.6391 |
| 1.052 | 4.0 | 520 | 1.0410 | 0.6165 |
| 1.0519 | 5.0 | 650 | 1.0324 | 0.6917 |
### Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.0
- Datasets 2.15.1.dev0
- Tokenizers 0.20.0
|