|
--- |
|
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 |
|
|
