---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: spermatogenesis-classifier-v2
  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. -->

# spermatogenesis-classifier-v2

This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4213
- Accuracy: 0.8506
- F1: 0.8497
- Acc I-iv: 0.6970
- Acc Ix-x: 0.8571
- Acc V-vi: 0.8571
- Acc Vii-vii: 0.9574
- Acc Xi- xii: 0.8387

## 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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- num_epochs: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Acc I-iv | Acc Ix-x | Acc V-vi | Acc Vii-vii | Acc Xi- xii |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------:|:--------:|:--------:|:-----------:|:-----------:|
| 0.9761        | 1.0   | 25   | 1.0469          | 0.5977   | 0.5529 | 0.3030   | 0.0476   | 0.8571   | 0.9787      | 0.3548      |
| 0.8169        | 2.0   | 50   | 0.8854          | 0.6839   | 0.6571 | 0.2424   | 0.9048   | 0.8810   | 0.8936      | 0.4194      |
| 0.6579        | 3.0   | 75   | 0.9098          | 0.6782   | 0.6655 | 0.2727   | 0.9048   | 0.9762   | 0.6809      | 0.5484      |
| 0.3899        | 4.0   | 100  | 0.5647          | 0.7874   | 0.7882 | 0.6364   | 0.9048   | 0.7857   | 0.8936      | 0.7097      |
| 0.5074        | 5.0   | 125  | 1.0395          | 0.6609   | 0.6200 | 0.0909   | 1.0      | 0.9762   | 0.7447      | 0.4839      |
| 0.4786        | 6.0   | 150  | 0.5871          | 0.7816   | 0.7842 | 0.6364   | 0.9048   | 0.8333   | 0.8298      | 0.7097      |
| 0.3498        | 7.0   | 175  | 0.8465          | 0.6897   | 0.6908 | 0.7576   | 0.8095   | 0.5476   | 0.5745      | 0.9032      |
| 0.3699        | 8.0   | 200  | 0.4213          | 0.8506   | 0.8497 | 0.6970   | 0.8571   | 0.8571   | 0.9574      | 0.8387      |
| 0.5555        | 9.0   | 225  | 0.5174          | 0.7874   | 0.7892 | 0.6667   | 0.8571   | 0.8333   | 0.8298      | 0.7419      |
| 0.2530        | 10.0  | 250  | 0.7004          | 0.7989   | 0.7994 | 0.7576   | 0.8571   | 0.7857   | 0.9362      | 0.6129      |
| 0.2849        | 11.0  | 275  | 0.5274          | 0.8103   | 0.8078 | 0.6061   | 0.8095   | 0.9286   | 0.9149      | 0.7097      |
| 0.1722        | 12.0  | 300  | 0.5315          | 0.7931   | 0.7934 | 0.7879   | 0.8571   | 0.5714   | 0.9362      | 0.8387      |
| 0.1955        | 13.0  | 325  | 0.9076          | 0.7644   | 0.7517 | 0.4545   | 0.8571   | 0.9048   | 0.9787      | 0.5161      |


### Framework versions

- Transformers 5.6.2
- Pytorch 2.11.0+cu130
- Tokenizers 0.22.2