---
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dino-base-2023_10_31-demo-v5
  results: []
pipeline_tag: image-classification
---

<!-- 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. -->

# dino-base-2023_10_31-demo-v5

This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0993
- F1 Micro: 0.8523
- F1 Macro: 0.7900
- Roc Auc: 0.9054
- Accuracy: 0.5712

## 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: 0.01
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-------:|:--------:|
| 0.1686        | 1.0   | 592   | 0.1334          | 0.8014   | 0.7001   | 0.8691  | 0.5017   |
| 0.1255        | 2.0   | 1184  | 0.1214          | 0.8129   | 0.7228   | 0.8768  | 0.5180   |
| 0.1167        | 3.0   | 1776  | 0.1210          | 0.8167   | 0.7202   | 0.8714  | 0.5259   |
| 0.1087        | 4.0   | 2368  | 0.1209          | 0.8215   | 0.7468   | 0.8967  | 0.5136   |
| 0.1078        | 5.0   | 2960  | 0.1179          | 0.8135   | 0.7248   | 0.8640  | 0.5323   |
| 0.0992        | 6.0   | 3552  | 0.1169          | 0.8280   | 0.7482   | 0.9010  | 0.5224   |
| 0.0961        | 7.0   | 4144  | 0.1144          | 0.8311   | 0.7605   | 0.9004  | 0.5209   |
| 0.0939        | 8.0   | 4736  | 0.1107          | 0.8393   | 0.7503   | 0.9092  | 0.5298   |
| 0.0942        | 9.0   | 5328  | 0.1157          | 0.8249   | 0.7416   | 0.8762  | 0.5515   |
| 0.0922        | 10.0  | 5920  | 0.1072          | 0.8364   | 0.7776   | 0.8973  | 0.5481   |
| 0.0895        | 11.0  | 6512  | 0.1102          | 0.8310   | 0.7631   | 0.8890  | 0.5328   |
| 0.0866        | 12.0  | 7104  | 0.1054          | 0.8473   | 0.7701   | 0.9099  | 0.5451   |
| 0.0872        | 13.0  | 7696  | 0.1055          | 0.8454   | 0.7851   | 0.9097  | 0.5436   |
| 0.085         | 14.0  | 8288  | 0.1069          | 0.8422   | 0.7684   | 0.9008  | 0.5559   |
| 0.0854        | 15.0  | 8880  | 0.1106          | 0.8316   | 0.7666   | 0.8926  | 0.5456   |
| 0.0841        | 16.0  | 9472  | 0.1068          | 0.8405   | 0.7681   | 0.8922  | 0.5702   |
| 0.0807        | 17.0  | 10064 | 0.1041          | 0.8460   | 0.7814   | 0.9051  | 0.5594   |
| 0.0819        | 18.0  | 10656 | 0.1053          | 0.8431   | 0.7822   | 0.9046  | 0.5466   |
| 0.0801        | 19.0  | 11248 | 0.1081          | 0.8395   | 0.7683   | 0.9063  | 0.5436   |
| 0.0795        | 20.0  | 11840 | 0.1077          | 0.8451   | 0.7721   | 0.8980  | 0.5520   |
| 0.0798        | 21.0  | 12432 | 0.1069          | 0.8390   | 0.7721   | 0.8839  | 0.5742   |
| 0.0784        | 22.0  | 13024 | 0.1050          | 0.8442   | 0.7847   | 0.9059  | 0.5461   |
| 0.0775        | 23.0  | 13616 | 0.1065          | 0.8443   | 0.7904   | 0.9072  | 0.5476   |
| 0.0727        | 24.0  | 14208 | 0.1010          | 0.8493   | 0.7910   | 0.9051  | 0.5678   |
| 0.0707        | 25.0  | 14800 | 0.1002          | 0.8496   | 0.7877   | 0.9058  | 0.5643   |
| 0.0697        | 26.0  | 15392 | 0.1006          | 0.8489   | 0.7886   | 0.9024  | 0.5692   |
| 0.0699        | 27.0  | 15984 | 0.1005          | 0.8531   | 0.7897   | 0.9054  | 0.5702   |
| 0.0692        | 28.0  | 16576 | 0.1001          | 0.8499   | 0.7894   | 0.9059  | 0.5663   |
| 0.0719        | 29.0  | 17168 | 0.0998          | 0.8524   | 0.7854   | 0.9058  | 0.5737   |
| 0.0686        | 30.0  | 17760 | 0.1006          | 0.8503   | 0.7897   | 0.9033  | 0.5663   |
| 0.0692        | 31.0  | 18352 | 0.1000          | 0.8519   | 0.7928   | 0.9055  | 0.5717   |
| 0.0707        | 32.0  | 18944 | 0.1000          | 0.8517   | 0.7862   | 0.9056  | 0.5737   |
| 0.0695        | 33.0  | 19536 | 0.1002          | 0.8517   | 0.7850   | 0.9012  | 0.5781   |
| 0.069         | 34.0  | 20128 | 0.1008          | 0.8477   | 0.7849   | 0.9003  | 0.5658   |
| 0.0686        | 35.0  | 20720 | 0.1004          | 0.8523   | 0.7866   | 0.9009  | 0.5732   |
| 0.0688        | 36.0  | 21312 | 0.0994          | 0.8517   | 0.7902   | 0.9058  | 0.5673   |
| 0.0688        | 37.0  | 21904 | 0.0994          | 0.8523   | 0.7900   | 0.9048  | 0.5732   |
| 0.0677        | 38.0  | 22496 | 0.0994          | 0.8520   | 0.7905   | 0.9051  | 0.5697   |
| 0.0678        | 39.0  | 23088 | 0.0995          | 0.8516   | 0.7911   | 0.9035  | 0.5747   |
| 0.068         | 40.0  | 23680 | 0.0994          | 0.8520   | 0.7888   | 0.9039  | 0.5712   |
| 0.0679        | 41.0  | 24272 | 0.0994          | 0.8535   | 0.7908   | 0.9056  | 0.5757   |
| 0.0682        | 42.0  | 24864 | 0.0993          | 0.8517   | 0.7883   | 0.9054  | 0.5707   |
| 0.0677        | 43.0  | 25456 | 0.0994          | 0.8516   | 0.7908   | 0.9052  | 0.5707   |
| 0.0678        | 44.0  | 26048 | 0.0995          | 0.8518   | 0.7916   | 0.9066  | 0.5673   |
| 0.0677        | 45.0  | 26640 | 0.0993          | 0.8519   | 0.7886   | 0.9054  | 0.5702   |
| 0.0684        | 46.0  | 27232 | 0.0995          | 0.8519   | 0.7909   | 0.9060  | 0.5697   |
| 0.0675        | 47.0  | 27824 | 0.0994          | 0.8524   | 0.7908   | 0.9048  | 0.5757   |
| 0.067         | 48.0  | 28416 | 0.0995          | 0.8521   | 0.7893   | 0.9044  | 0.5717   |
| 0.0675        | 49.0  | 29008 | 0.0994          | 0.8524   | 0.7902   | 0.9056  | 0.5707   |
| 0.0674        | 50.0  | 29600 | 0.0994          | 0.8517   | 0.7893   | 0.9051  | 0.5692   |
| 0.0679        | 51.0  | 30192 | 0.0993          | 0.8519   | 0.7898   | 0.9052  | 0.5697   |
| 0.0667        | 52.0  | 30784 | 0.0993          | 0.8523   | 0.7900   | 0.9054  | 0.5712   |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1