metadata
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-base-imagenet1k-1-layer
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_awesome_food_model
results: []
my_awesome_food_model
This model is a fine-tuned version of facebook/dinov2-base-imagenet1k-1-layer on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1930
- Accuracy: 0.943
This is just a model created by following the the Tramnformers tutorial on image classification at https://huggingface.co/docs/transformers/main/en/tasks/image_classification
So quite worthless
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3989 | 0.992 | 62 | 0.3865 | 0.867 |
| 0.2722 | 2.0 | 125 | 0.2720 | 0.916 |
| 0.126 | 2.976 | 186 | 0.1930 | 0.943 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0