---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dinov2-large-MEG7-10
  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-large-MEG7-10

This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3278
- Accuracy: 0.9324

## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 0.354         | 0.9999 | 5312  | 0.4495          | 0.8662   |
| 0.2705        | 2.0    | 10625 | 0.3835          | 0.8900   |
| 0.2003        | 2.9999 | 15937 | 0.3546          | 0.9021   |
| 0.2712        | 4.0    | 21250 | 0.3297          | 0.9060   |
| 0.2028        | 4.9999 | 26562 | 0.3259          | 0.9099   |
| 0.1638        | 6.0    | 31875 | 0.3087          | 0.9183   |
| 0.1289        | 6.9999 | 37187 | 0.3260          | 0.9195   |
| 0.0752        | 8.0    | 42500 | 0.3197          | 0.9256   |
| 0.0643        | 8.9999 | 47812 | 0.3229          | 0.9276   |
| 0.0509        | 9.9991 | 53120 | 0.3278          | 0.9324   |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.20.3