---
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: datrix-image-classification-job_5472a213
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.25660377358490566
---

<!-- 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. -->

# datrix-image-classification-job_5472a213

This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 2.7470
- Accuracy: 0.2566

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.5699        | 1.0   | 239  | 3.5545          | 0.0642   |
| 3.3479        | 2.0   | 478  | 3.3057          | 0.1170   |
| 3.2327        | 3.0   | 717  | 3.1975          | 0.1208   |
| 3.1248        | 4.0   | 956  | 3.0876          | 0.1434   |
| 3.0689        | 5.0   | 1195 | 2.9798          | 0.1736   |
| 2.9669        | 6.0   | 1434 | 2.9051          | 0.2038   |
| 2.9706        | 7.0   | 1673 | 2.8224          | 0.2151   |
| 2.9171        | 8.0   | 1912 | 2.7895          | 0.2528   |
| 2.8688        | 9.0   | 2151 | 2.7562          | 0.2528   |
| 2.8695        | 10.0  | 2390 | 2.7470          | 0.2566   |


### Framework versions

- Transformers 5.9.0
- Pytorch 2.12.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2