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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: 0.6875
- Accuracy: 0.8647
## 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: 20.0
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.0864 | 1.0 | 130 | 0.4286 | 1.0878 |
| 1.0629 | 2.0 | 260 | 0.5489 | 1.0594 |
| 1.0434 | 3.0 | 390 | 0.6767 | 1.0230 |
| 1.0214 | 4.0 | 520 | 0.6767 | 0.9965 |
| 1.0026 | 5.0 | 650 | 0.7444 | 0.9569 |
| 0.9753 | 6.0 | 780 | 0.7820 | 0.9288 |
| 0.9252 | 7.0 | 910 | 0.7970 | 0.8875 |
| 0.9192 | 8.0 | 1040 | 0.8120 | 0.8506 |
| 0.9008 | 9.0 | 1170 | 0.8045 | 0.8338 |
| 0.8079 | 10.0 | 1300 | 0.8421 | 0.8104 |
| 0.8332 | 11.0 | 1430 | 0.8346 | 0.7806 |
| 0.8103 | 12.0 | 1560 | 0.8346 | 0.7586 |
| 0.8149 | 13.0 | 1690 | 0.8421 | 0.7571 |
| 0.8186 | 14.0 | 1820 | 0.8271 | 0.7540 |
| 0.7929 | 15.0 | 1950 | 0.8120 | 0.7412 |
| 0.774 | 16.0 | 2080 | 0.7370 | 0.8496 |
| 0.7613 | 17.0 | 2210 | 0.7059 | 0.8496 |
| 0.7778 | 18.0 | 2340 | 0.6930 | 0.8271 |
| 0.8081 | 19.0 | 2470 | 0.6890 | 0.8647 |
| 0.7916 | 20.0 | 2600 | 0.6875 | 0.8647 |
### Framework versions
- Transformers 4.47.0.dev0
- Pytorch 2.4.1+cu118
- Datasets 2.21.0
- Tokenizers 0.20.0
|