metadata
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: dinov2-finetuned-har
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: 0.9148148148148149
dinov2-finetuned-har
This model is a fine-tuned version of facebook/dinov2-base on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.3078
- Accuracy: 0.9148
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- 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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.9429 | 0.9910 | 83 | 0.5624 | 0.8328 |
| 0.7912 | 1.9940 | 167 | 0.4755 | 0.8587 |
| 0.7371 | 2.9970 | 251 | 0.4584 | 0.8550 |
| 0.5915 | 4.0 | 335 | 0.3870 | 0.8762 |
| 0.5635 | 4.9910 | 418 | 0.4037 | 0.8704 |
| 0.498 | 5.9940 | 502 | 0.3876 | 0.8804 |
| 0.4541 | 6.9970 | 586 | 0.3612 | 0.8884 |
| 0.3513 | 8.0 | 670 | 0.3240 | 0.9053 |
| 0.2963 | 8.9910 | 753 | 0.3176 | 0.9116 |
| 0.2815 | 9.9104 | 830 | 0.3078 | 0.9148 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1