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---
license: apache-2.0
base_model: facebook/dinov2-giant
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: dino_finetuned_giant_10_layers_thawed
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.7361218408564176
---
<!-- 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. -->
# dino_finetuned_giant_10_layers_thawed
This model is a fine-tuned version of [facebook/dinov2-giant](https://huggingface.co/facebook/dinov2-giant) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0387
- Accuracy: 0.7361
## 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: 54
- eval_batch_size: 54
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 216
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 3.3778 | 0.3145 | 25 | 2.5161 | 0.3373 |
| 2.0106 | 0.6289 | 50 | 1.8874 | 0.4838 |
| 1.9 | 0.9434 | 75 | 1.6407 | 0.5441 |
| 1.2966 | 1.2579 | 100 | 1.4907 | 0.5930 |
| 1.3413 | 1.5723 | 125 | 1.3532 | 0.6358 |
| 1.2871 | 1.8868 | 150 | 1.2731 | 0.6547 |
| 0.7792 | 2.2013 | 175 | 1.1967 | 0.6875 |
| 0.7153 | 2.5157 | 200 | 1.1761 | 0.6966 |
| 0.7544 | 2.8302 | 225 | 1.1136 | 0.7096 |
| 0.465 | 3.1447 | 250 | 1.0962 | 0.7187 |
| 0.414 | 3.4591 | 275 | 1.0997 | 0.7274 |
| 0.4749 | 3.7736 | 300 | 1.0717 | 0.7291 |
| 0.4742 | 4.0881 | 325 | 1.0425 | 0.7323 |
| 0.3448 | 4.4025 | 350 | 1.0402 | 0.7392 |
| 0.3341 | 4.7170 | 375 | 1.0387 | 0.7361 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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