transformers safetensors dinov2 image-classification generated_from_trainer base_model:facebook/dinov2-base-imagenet1k-1-layer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/dinov2-base-imagenet1k-1-layer
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Foot
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Foot

This model is a fine-tuned version of [facebook/dinov2-base-imagenet1k-1-layer](https://huggingface.co/facebook/dinov2-base-imagenet1k-1-layer) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0747
- Accuracy: 0.4865

## 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: 5e-05
- train_batch_size: 10
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 20
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 1.0   | 2    | 1.2201          | 0.3378   |
| No log        | 2.0   | 4    | 1.2243          | 0.2568   |
| No log        | 3.0   | 6    | 1.2672          | 0.2703   |
| No log        | 4.0   | 8    | 1.2501          | 0.2297   |
| 1.2006        | 5.0   | 10   | 1.1975          | 0.2973   |
| 1.2006        | 6.0   | 12   | 1.1270          | 0.3919   |
| 1.2006        | 7.0   | 14   | 1.0999          | 0.3243   |
| 1.2006        | 8.0   | 16   | 1.1497          | 0.3649   |
| 1.2006        | 9.0   | 18   | 1.1006          | 0.3108   |
| 1.1058        | 10.0  | 20   | 1.1271          | 0.3514   |
| 1.1058        | 11.0  | 22   | 1.1273          | 0.3784   |
| 1.1058        | 12.0  | 24   | 1.1639          | 0.2838   |
| 1.1058        | 13.0  | 26   | 1.1421          | 0.4054   |
| 1.1058        | 14.0  | 28   | 1.1190          | 0.3514   |
| 1.0489        | 15.0  | 30   | 1.1735          | 0.3243   |
| 1.0489        | 16.0  | 32   | 1.1422          | 0.3378   |
| 1.0489        | 17.0  | 34   | 1.1414          | 0.3649   |
| 1.0489        | 18.0  | 36   | 1.1033          | 0.4189   |
| 1.0489        | 19.0  | 38   | 1.0747          | 0.3919   |
| 0.9717        | 20.0  | 40   | 1.0952          | 0.3919   |
| 0.9717        | 21.0  | 42   | 1.1063          | 0.3784   |
| 0.9717        | 22.0  | 44   | 1.0822          | 0.3649   |
| 0.9717        | 23.0  | 46   | 1.0768          | 0.3784   |
| 0.9717        | 24.0  | 48   | 1.0753          | 0.4595   |
| 0.9816        | 25.0  | 50   | 1.0531          | 0.4054   |
| 0.9816        | 26.0  | 52   | 1.0624          | 0.4189   |
| 0.9816        | 27.0  | 54   | 1.0690          | 0.4459   |
| 0.9816        | 28.0  | 56   | 1.1392          | 0.3514   |
| 0.9816        | 29.0  | 58   | 1.0696          | 0.4054   |
| 0.9576        | 30.0  | 60   | 1.0747          | 0.4865   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
