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--- |
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license: apache-2.0 |
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base_model: facebook/dinov2-base-imagenet1k-1-layer |
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tags: |
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- image-classification |
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- vision |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: dinov2-base-imagenet1k-1-layer-finetuned-galaxy10-decals |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# dinov2-base-imagenet1k-1-layer-finetuned-galaxy10-decals |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5267 |
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- Accuracy: 0.8670 |
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- Precision: 0.8645 |
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- Recall: 0.8670 |
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- F1: 0.8650 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.8157 | 0.99 | 62 | 0.6740 | 0.7813 | 0.8046 | 0.7813 | 0.7853 | |
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| 0.8091 | 2.0 | 125 | 0.5948 | 0.8021 | 0.8016 | 0.8021 | 0.7950 | |
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| 0.6983 | 2.99 | 187 | 0.6016 | 0.7965 | 0.8077 | 0.7965 | 0.7909 | |
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| 0.6701 | 4.0 | 250 | 0.5676 | 0.7982 | 0.8016 | 0.7982 | 0.7954 | |
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| 0.5998 | 4.99 | 312 | 0.5116 | 0.8286 | 0.8401 | 0.8286 | 0.8302 | |
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| 0.5521 | 6.0 | 375 | 0.5155 | 0.8354 | 0.8375 | 0.8354 | 0.8325 | |
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| 0.5441 | 6.99 | 437 | 0.5574 | 0.8033 | 0.8104 | 0.8033 | 0.7980 | |
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| 0.5142 | 8.0 | 500 | 0.4818 | 0.8410 | 0.8418 | 0.8410 | 0.8376 | |
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| 0.5136 | 8.99 | 562 | 0.4914 | 0.8337 | 0.8353 | 0.8337 | 0.8317 | |
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| 0.4533 | 10.0 | 625 | 0.4740 | 0.8320 | 0.8335 | 0.8320 | 0.8295 | |
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| 0.4904 | 10.99 | 687 | 0.5075 | 0.8399 | 0.8409 | 0.8399 | 0.8375 | |
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| 0.4361 | 12.0 | 750 | 0.4552 | 0.8563 | 0.8554 | 0.8563 | 0.8540 | |
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| 0.414 | 12.99 | 812 | 0.5025 | 0.8365 | 0.8455 | 0.8365 | 0.8374 | |
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| 0.4114 | 14.0 | 875 | 0.4822 | 0.8467 | 0.8437 | 0.8467 | 0.8420 | |
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| 0.3878 | 14.99 | 937 | 0.4615 | 0.8574 | 0.8552 | 0.8574 | 0.8549 | |
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| 0.3756 | 16.0 | 1000 | 0.5017 | 0.8444 | 0.8523 | 0.8444 | 0.8449 | |
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| 0.3056 | 16.99 | 1062 | 0.4910 | 0.8517 | 0.8495 | 0.8517 | 0.8501 | |
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| 0.3255 | 18.0 | 1125 | 0.5206 | 0.8523 | 0.8505 | 0.8523 | 0.8491 | |
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| 0.3224 | 18.99 | 1187 | 0.5066 | 0.8450 | 0.8470 | 0.8450 | 0.8438 | |
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| 0.2763 | 20.0 | 1250 | 0.5043 | 0.8574 | 0.8519 | 0.8574 | 0.8534 | |
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| 0.2926 | 20.99 | 1312 | 0.5345 | 0.8546 | 0.8542 | 0.8546 | 0.8512 | |
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| 0.2824 | 22.0 | 1375 | 0.5320 | 0.8529 | 0.8523 | 0.8529 | 0.8517 | |
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| 0.2613 | 22.99 | 1437 | 0.5254 | 0.8563 | 0.8543 | 0.8563 | 0.8542 | |
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| 0.2292 | 24.0 | 1500 | 0.5553 | 0.8546 | 0.8529 | 0.8546 | 0.8528 | |
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| 0.2313 | 24.99 | 1562 | 0.5603 | 0.8602 | 0.8612 | 0.8602 | 0.8593 | |
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| 0.2143 | 26.0 | 1625 | 0.5267 | 0.8670 | 0.8645 | 0.8670 | 0.8650 | |
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| 0.2075 | 26.99 | 1687 | 0.5737 | 0.8574 | 0.8589 | 0.8574 | 0.8573 | |
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| 0.2121 | 28.0 | 1750 | 0.5748 | 0.8619 | 0.8601 | 0.8619 | 0.8604 | |
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| 0.1944 | 28.99 | 1812 | 0.5666 | 0.8647 | 0.8618 | 0.8647 | 0.8624 | |
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| 0.1866 | 29.76 | 1860 | 0.5676 | 0.8608 | 0.8583 | 0.8608 | 0.8589 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.3.0 |
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- Datasets 2.19.1 |
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- Tokenizers 0.15.1 |
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