---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-small-imagenet1k-1-layer
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dinov2-small-imagenet1k-1-layer-finetuned-noh
  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. -->

# dinov2-small-imagenet1k-1-layer-finetuned-noh

This model is a fine-tuned version of [facebook/dinov2-small-imagenet1k-1-layer](https://huggingface.co/facebook/dinov2-small-imagenet1k-1-layer) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3058
- Accuracy: 0.8982

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5315        | 1.0    | 23   | 1.2674          | 0.2479   |
| 0.4629        | 2.0    | 46   | 0.5134          | 0.7882   |
| 0.4368        | 3.0    | 69   | 0.3058          | 0.8982   |
| 0.4123        | 4.0    | 92   | 0.4148          | 0.8046   |
| 0.3301        | 5.0    | 115  | 0.3520          | 0.8736   |
| 0.2907        | 6.0    | 138  | 0.4415          | 0.8440   |
| 0.2809        | 7.0    | 161  | 0.5786          | 0.7521   |
| 0.2243        | 8.0    | 184  | 0.4724          | 0.8752   |
| 0.1968        | 9.0    | 207  | 0.5452          | 0.8703   |
| 0.1601        | 9.5778 | 220  | 0.5386          | 0.8440   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1
- Datasets 2.19.1
- Tokenizers 0.21.0