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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/convnextv2-large-1k-224
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+ tags:
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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: convnextv2-large-1k-224-finetuned-galaxy10-decals
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+ results: []
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+ ---
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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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+
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+ # convnextv2-large-1k-224-finetuned-galaxy10-decals
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+
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+ This model is a fine-tuned version of [facebook/convnextv2-large-1k-224](https://huggingface.co/facebook/convnextv2-large-1k-224) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.4970
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+ - Accuracy: 0.8630
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+ - Precision: 0.8615
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+ - Recall: 0.8630
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+ - F1: 0.8617
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 1.9261 | 0.99 | 62 | 1.8153 | 0.4696 | 0.5070 | 0.4696 | 0.3875 |
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+ | 1.2684 | 2.0 | 125 | 1.1432 | 0.6793 | 0.6395 | 0.6793 | 0.6478 |
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+ | 0.9177 | 2.99 | 187 | 0.7477 | 0.7847 | 0.7832 | 0.7847 | 0.7720 |
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+ | 0.6937 | 4.0 | 250 | 0.5962 | 0.8168 | 0.8145 | 0.8168 | 0.8104 |
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+ | 0.5937 | 4.99 | 312 | 0.5862 | 0.8191 | 0.8234 | 0.8191 | 0.8167 |
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+ | 0.5921 | 6.0 | 375 | 0.5389 | 0.8365 | 0.8454 | 0.8365 | 0.8300 |
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+ | 0.557 | 6.99 | 437 | 0.4944 | 0.8433 | 0.8478 | 0.8433 | 0.8410 |
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+ | 0.5522 | 8.0 | 500 | 0.5022 | 0.8427 | 0.8508 | 0.8427 | 0.8416 |
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+ | 0.5028 | 8.99 | 562 | 0.4481 | 0.8579 | 0.8610 | 0.8579 | 0.8580 |
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+ | 0.4801 | 10.0 | 625 | 0.4360 | 0.8551 | 0.8536 | 0.8551 | 0.8527 |
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+ | 0.4475 | 10.99 | 687 | 0.4663 | 0.8410 | 0.8423 | 0.8410 | 0.8407 |
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+ | 0.411 | 12.0 | 750 | 0.4444 | 0.8546 | 0.8552 | 0.8546 | 0.8538 |
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+ | 0.4173 | 12.99 | 812 | 0.4341 | 0.8613 | 0.8627 | 0.8613 | 0.8595 |
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+ | 0.3995 | 14.0 | 875 | 0.4380 | 0.8653 | 0.8655 | 0.8653 | 0.8637 |
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+ | 0.3657 | 14.99 | 937 | 0.4659 | 0.8625 | 0.8633 | 0.8625 | 0.8615 |
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+ | 0.3533 | 16.0 | 1000 | 0.4600 | 0.8602 | 0.8592 | 0.8602 | 0.8585 |
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+ | 0.3001 | 16.99 | 1062 | 0.5069 | 0.8478 | 0.8455 | 0.8478 | 0.8450 |
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+ | 0.318 | 18.0 | 1125 | 0.4647 | 0.8574 | 0.8576 | 0.8574 | 0.8552 |
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+ | 0.3029 | 18.99 | 1187 | 0.4479 | 0.8681 | 0.8670 | 0.8681 | 0.8668 |
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+ | 0.2915 | 20.0 | 1250 | 0.4772 | 0.8625 | 0.8598 | 0.8625 | 0.8586 |
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+ | 0.2742 | 20.99 | 1312 | 0.4798 | 0.8557 | 0.8538 | 0.8557 | 0.8521 |
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+ | 0.3067 | 22.0 | 1375 | 0.4767 | 0.8602 | 0.8573 | 0.8602 | 0.8575 |
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+ | 0.2758 | 22.99 | 1437 | 0.5099 | 0.8506 | 0.8547 | 0.8506 | 0.8516 |
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+ | 0.2527 | 24.0 | 1500 | 0.5016 | 0.8585 | 0.8563 | 0.8585 | 0.8565 |
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+ | 0.253 | 24.99 | 1562 | 0.4990 | 0.8625 | 0.8605 | 0.8625 | 0.8604 |
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+ | 0.2361 | 26.0 | 1625 | 0.4903 | 0.8602 | 0.8590 | 0.8602 | 0.8591 |
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+ | 0.2325 | 26.99 | 1687 | 0.5062 | 0.8602 | 0.8612 | 0.8602 | 0.8600 |
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+ | 0.2448 | 28.0 | 1750 | 0.4997 | 0.8670 | 0.8648 | 0.8670 | 0.8646 |
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+ | 0.2354 | 28.99 | 1812 | 0.4956 | 0.8608 | 0.8586 | 0.8608 | 0.8590 |
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+ | 0.2156 | 29.76 | 1860 | 0.4970 | 0.8630 | 0.8615 | 0.8630 | 0.8617 |
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+
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+
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+ ### Framework versions
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+
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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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