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---
license: apache-2.0
base_model: facebook/dinov2-base-imagenet1k-1-layer
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: dinov2-base-imagenet1k-1-layer-finetuned-galaxy10-decals
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-base-imagenet1k-1-layer-finetuned-galaxy10-decals
This model is a fine-tuned version of [facebook/dinov2-base-imagenet1k-1-layer](https://huggingface.co/facebook/dinov2-base-imagenet1k-1-layer) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5267
- Accuracy: 0.8670
- Precision: 0.8645
- Recall: 0.8670
- F1: 0.8650
## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.8157 | 0.99 | 62 | 0.6740 | 0.7813 | 0.8046 | 0.7813 | 0.7853 |
| 0.8091 | 2.0 | 125 | 0.5948 | 0.8021 | 0.8016 | 0.8021 | 0.7950 |
| 0.6983 | 2.99 | 187 | 0.6016 | 0.7965 | 0.8077 | 0.7965 | 0.7909 |
| 0.6701 | 4.0 | 250 | 0.5676 | 0.7982 | 0.8016 | 0.7982 | 0.7954 |
| 0.5998 | 4.99 | 312 | 0.5116 | 0.8286 | 0.8401 | 0.8286 | 0.8302 |
| 0.5521 | 6.0 | 375 | 0.5155 | 0.8354 | 0.8375 | 0.8354 | 0.8325 |
| 0.5441 | 6.99 | 437 | 0.5574 | 0.8033 | 0.8104 | 0.8033 | 0.7980 |
| 0.5142 | 8.0 | 500 | 0.4818 | 0.8410 | 0.8418 | 0.8410 | 0.8376 |
| 0.5136 | 8.99 | 562 | 0.4914 | 0.8337 | 0.8353 | 0.8337 | 0.8317 |
| 0.4533 | 10.0 | 625 | 0.4740 | 0.8320 | 0.8335 | 0.8320 | 0.8295 |
| 0.4904 | 10.99 | 687 | 0.5075 | 0.8399 | 0.8409 | 0.8399 | 0.8375 |
| 0.4361 | 12.0 | 750 | 0.4552 | 0.8563 | 0.8554 | 0.8563 | 0.8540 |
| 0.414 | 12.99 | 812 | 0.5025 | 0.8365 | 0.8455 | 0.8365 | 0.8374 |
| 0.4114 | 14.0 | 875 | 0.4822 | 0.8467 | 0.8437 | 0.8467 | 0.8420 |
| 0.3878 | 14.99 | 937 | 0.4615 | 0.8574 | 0.8552 | 0.8574 | 0.8549 |
| 0.3756 | 16.0 | 1000 | 0.5017 | 0.8444 | 0.8523 | 0.8444 | 0.8449 |
| 0.3056 | 16.99 | 1062 | 0.4910 | 0.8517 | 0.8495 | 0.8517 | 0.8501 |
| 0.3255 | 18.0 | 1125 | 0.5206 | 0.8523 | 0.8505 | 0.8523 | 0.8491 |
| 0.3224 | 18.99 | 1187 | 0.5066 | 0.8450 | 0.8470 | 0.8450 | 0.8438 |
| 0.2763 | 20.0 | 1250 | 0.5043 | 0.8574 | 0.8519 | 0.8574 | 0.8534 |
| 0.2926 | 20.99 | 1312 | 0.5345 | 0.8546 | 0.8542 | 0.8546 | 0.8512 |
| 0.2824 | 22.0 | 1375 | 0.5320 | 0.8529 | 0.8523 | 0.8529 | 0.8517 |
| 0.2613 | 22.99 | 1437 | 0.5254 | 0.8563 | 0.8543 | 0.8563 | 0.8542 |
| 0.2292 | 24.0 | 1500 | 0.5553 | 0.8546 | 0.8529 | 0.8546 | 0.8528 |
| 0.2313 | 24.99 | 1562 | 0.5603 | 0.8602 | 0.8612 | 0.8602 | 0.8593 |
| 0.2143 | 26.0 | 1625 | 0.5267 | 0.8670 | 0.8645 | 0.8670 | 0.8650 |
| 0.2075 | 26.99 | 1687 | 0.5737 | 0.8574 | 0.8589 | 0.8574 | 0.8573 |
| 0.2121 | 28.0 | 1750 | 0.5748 | 0.8619 | 0.8601 | 0.8619 | 0.8604 |
| 0.1944 | 28.99 | 1812 | 0.5666 | 0.8647 | 0.8618 | 0.8647 | 0.8624 |
| 0.1866 | 29.76 | 1860 | 0.5676 | 0.8608 | 0.8583 | 0.8608 | 0.8589 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1
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