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---
library_name: transformers
license: apache-2.0
base_model: microsoft/resnet-18
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: vit-finetuned2
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-finetuned2
This model is a fine-tuned version of [microsoft/resnet-18](https://huggingface.co/microsoft/resnet-18) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8828
- Accuracy: 0.746
## 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: 0.0002
- train_batch_size: 64
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.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
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 211 | 3.2058 | 0.2 |
| No log | 2.0 | 422 | 2.7863 | 0.27 |
| 3.5109 | 3.0 | 633 | 2.6225 | 0.306 |
| 3.5109 | 4.0 | 844 | 2.3383 | 0.392 |
| 2.6956 | 5.0 | 1055 | 2.1045 | 0.456 |
| 2.6956 | 6.0 | 1266 | 1.8551 | 0.504 |
| 2.6956 | 7.0 | 1477 | 1.6949 | 0.54 |
| 2.213 | 8.0 | 1688 | 1.5866 | 0.576 |
| 2.213 | 9.0 | 1899 | 1.3373 | 0.646 |
| 1.8406 | 10.0 | 2110 | 1.2958 | 0.64 |
| 1.8406 | 11.0 | 2321 | 1.3066 | 0.652 |
| 1.5618 | 12.0 | 2532 | 1.1972 | 0.664 |
| 1.5618 | 13.0 | 2743 | 1.1654 | 0.67 |
| 1.5618 | 14.0 | 2954 | 1.0900 | 0.7 |
| 1.3308 | 15.0 | 3165 | 1.0244 | 0.704 |
| 1.3308 | 16.0 | 3376 | 1.0534 | 0.706 |
| 1.1426 | 17.0 | 3587 | 0.9758 | 0.732 |
| 1.1426 | 18.0 | 3798 | 0.9583 | 0.716 |
| 1.0085 | 19.0 | 4009 | 0.9191 | 0.732 |
| 1.0085 | 20.0 | 4220 | 0.8828 | 0.746 |
### Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1
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