---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: output_dinov2_large
  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. -->

# output_dinov2_large

This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0294
- Precision: 0.9810
- Recall: 0.9748
- F1: 0.9779

## 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: 2e-06
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| No log        | 1.0   | 145  | 0.0585          | 0.9332    | 0.9538 | 0.9434 |
| No log        | 2.0   | 290  | 0.0367          | 0.9527    | 0.9727 | 0.9626 |
| No log        | 3.0   | 435  | 0.0338          | 0.9776    | 0.9622 | 0.9698 |
| 1.3658        | 4.0   | 580  | 0.0265          | 0.9718    | 0.9769 | 0.9743 |
| 1.3658        | 5.0   | 725  | 0.0250          | 0.9708    | 0.9790 | 0.9749 |
| 1.3658        | 6.0   | 870  | 0.0323          | 0.9809    | 0.9695 | 0.9752 |
| 0.0959        | 7.0   | 1015 | 0.0285          | 0.9749    | 0.9800 | 0.9775 |
| 0.0959        | 8.0   | 1160 | 0.0319          | 0.9820    | 0.9727 | 0.9773 |
| 0.0959        | 9.0   | 1305 | 0.0313          | 0.9810    | 0.9737 | 0.9773 |
| 0.0959        | 10.0  | 1450 | 0.0294          | 0.9810    | 0.9748 | 0.9779 |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2