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---
license: apache-2.0
base_model: facebook/dinov2-small
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dinov2-small-types-of-film-shots-vN
  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-types-of-film-shots-vN

This model is a fine-tuned version of [facebook/dinov2-small](https://huggingface.co/facebook/dinov2-small) on the szymonrucinski/types-of-film-shots dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9864
- Accuracy: 0.6259

## 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: 4
- eval_batch_size: 4
- seed: 17480
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 12.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6177        | 0.97  | 24   | 1.5501          | 0.4101   |
| 1.3029        | 1.99  | 49   | 1.2448          | 0.5108   |
| 1.1785        | 2.96  | 73   | 1.0556          | 0.5252   |
| 1.2146        | 3.98  | 98   | 1.2316          | 0.5396   |
| 0.8389        | 4.99  | 123  | 1.0235          | 0.5971   |
| 0.7883        | 5.97  | 147  | 0.9960          | 0.6259   |
| 0.7899        | 6.98  | 172  | 1.1354          | 0.5540   |
| 0.663         | 8.0   | 197  | 1.0971          | 0.5827   |
| 0.6013        | 8.97  | 221  | 0.9864          | 0.6259   |
| 0.6276        | 9.99  | 246  | 1.0182          | 0.6115   |
| 0.5196        | 10.96 | 270  | 1.0074          | 0.6547   |
| 0.4761        | 11.7  | 288  | 0.9956          | 0.6763   |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2