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---
license: apache-2.0
base_model: facebook/dinov2-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: DinoVdeau-large-2024_10_25-prova_batch-size8_freeze_monolabel
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. -->
# DinoVdeau-large-2024_10_25-prova_batch-size8_freeze_monolabel
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: 2.8116
- F1 Micro: 0.5
- F1 Macro: 0.2126
- Accuracy: 0.5
- Learning Rate: 0.001
## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Accuracy | Rate |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|:-----:|
| No log | 1.0 | 7 | 2.7061 | 0.5 | 0.2790 | 0.5 | 0.001 |
### Framework versions
- Transformers 4.41.0
- Pytorch 2.5.0+cu124
- Datasets 3.0.2
- Tokenizers 0.19.1
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