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-base-fa-disabled-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: 0.9164021164021164
dinov2-base-fa-disabled-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: 0.3027
- Accuracy: 0.9164
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 |
|---|---|---|---|---|
| 0.8554 | 0.9910 | 83 | 0.5252 | 0.8323 |
| 0.8162 | 1.9940 | 167 | 0.4597 | 0.8598 |
| 0.7303 | 2.9970 | 251 | 0.4403 | 0.8587 |
| 0.5644 | 4.0 | 335 | 0.3922 | 0.8746 |
| 0.5672 | 4.9910 | 418 | 0.3784 | 0.8857 |
| 0.454 | 5.9940 | 502 | 0.3856 | 0.8831 |
| 0.4379 | 6.9970 | 586 | 0.3510 | 0.8889 |
| 0.3356 | 8.0 | 670 | 0.3187 | 0.9063 |
| 0.2877 | 8.9910 | 753 | 0.3209 | 0.9116 |
| 0.2717 | 9.9104 | 830 | 0.3027 | 0.9164 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1