transformers tensorboard safetensors dinov2 image-classification generated_from_trainer base_model:facebook/dinov2-base license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: outputs
  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. -->

# outputs

This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0742
- Precision: 0.9306
- Recall: 0.8969
- F1: 0.9135

## 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: 1e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.5948        | 0.98  | 39   | 0.4487          | 0.1103    | 0.0658 | 0.0824 |
| 0.2211        | 1.98  | 79   | 0.2079          | 0.8179    | 0.5614 | 0.6658 |
| 0.1241        | 2.98  | 119  | 0.1378          | 0.8880    | 0.7390 | 0.8067 |
| 0.0954        | 3.99  | 159  | 0.1117          | 0.8916    | 0.8114 | 0.8496 |
| 0.0801        | 4.99  | 199  | 0.0980          | 0.9167    | 0.8322 | 0.8724 |
| 0.0716        | 5.99  | 239  | 0.0875          | 0.9245    | 0.8596 | 0.8909 |
| 0.0641        | 7.0   | 279  | 0.0871          | 0.9231    | 0.8421 | 0.8807 |
| 0.0615        | 8.0   | 319  | 0.0804          | 0.9318    | 0.8838 | 0.9071 |
| 0.056         | 8.98  | 358  | 0.0793          | 0.9257    | 0.8882 | 0.9065 |
| 0.0541        | 9.98  | 398  | 0.0761          | 0.9335    | 0.8925 | 0.9126 |
| 0.0532        | 10.98 | 438  | 0.0767          | 0.9339    | 0.8827 | 0.9076 |
| 0.053         | 11.99 | 478  | 0.0758          | 0.9312    | 0.8904 | 0.9103 |
| 0.048         | 12.99 | 518  | 0.0743          | 0.9324    | 0.8925 | 0.9120 |
| 0.047         | 13.99 | 558  | 0.0750          | 0.9303    | 0.8925 | 0.9110 |
| 0.0476        | 14.67 | 585  | 0.0742          | 0.9306    | 0.8969 | 0.9135 |


### Framework versions

- Transformers 4.37.0
- Pytorch 1.13.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
