metadata
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
- f1
model-index:
- name: dinov2-base-finetuned-ct-iq
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: Accuracy
type: accuracy
value: 1
- name: F1
type: f1
value: 1
dinov2-base-finetuned-ct-iq
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: 0.0000
- Accuracy: 1.0
- F1: 1.0
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 | F1 |
|---|---|---|---|---|---|
| 0.0265 | 0.9954 | 162 | 0.2460 | 0.9233 | 0.9295 |
| 0.0185 | 1.9969 | 325 | 0.0023 | 1.0 | 1.0 |
| 0.1076 | 2.9985 | 488 | 0.0204 | 0.9939 | 0.9938 |
| 0.1424 | 4.0 | 651 | 0.0001 | 1.0 | 1.0 |
| 0.0002 | 4.9954 | 813 | 0.0013 | 1.0 | 1.0 |
| 0.0414 | 5.9969 | 976 | 0.0000 | 1.0 | 1.0 |
| 0.0003 | 6.9985 | 1139 | 0.0003 | 1.0 | 1.0 |
| 0.0011 | 8.0 | 1302 | 0.0163 | 0.9969 | 0.9969 |
| 0.0 | 8.9954 | 1464 | 0.0010 | 1.0 | 1.0 |
| 0.0 | 9.9539 | 1620 | 0.0000 | 1.0 | 1.0 |
Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.21.0
- Tokenizers 0.19.1