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convnextv2-tiny-1k-224-finetuned-galaxy10-decals

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  1. README.md +48 -34
  2. model.safetensors +1 -1
README.md CHANGED
@@ -2,11 +2,12 @@
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  license: apache-2.0
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  base_model: facebook/convnextv2-tiny-1k-224
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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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  model-index:
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  - name: convnextv2-tiny-1k-224-finetuned-galaxy10-decals
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  results: []
@@ -17,10 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
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  # convnextv2-tiny-1k-224-finetuned-galaxy10-decals
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- This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on the matthieulel/galaxy10_decals dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.4261
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- - Accuracy: 0.8703
 
 
 
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  ## Model description
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@@ -40,45 +44,55 @@ More information needed
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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: 32
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- - eval_batch_size: 32
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  - seed: 42
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  - gradient_accumulation_steps: 4
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- - total_train_batch_size: 128
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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: 20
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-------:|:----:|:---------------:|:--------:|
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- | 1.4287 | 0.9940 | 124 | 1.2978 | 0.5851 |
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- | 0.8329 | 1.9960 | 249 | 0.6987 | 0.7728 |
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- | 0.7348 | 2.9980 | 374 | 0.5659 | 0.8179 |
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- | 0.611 | 4.0 | 499 | 0.5379 | 0.8298 |
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- | 0.5929 | 4.9940 | 623 | 0.4972 | 0.8377 |
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- | 0.5227 | 5.9960 | 748 | 0.4715 | 0.8478 |
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- | 0.5166 | 6.9980 | 873 | 0.4761 | 0.8495 |
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- | 0.4992 | 8.0 | 998 | 0.4320 | 0.8563 |
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- | 0.4528 | 8.9940 | 1122 | 0.4410 | 0.8641 |
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- | 0.4566 | 9.9960 | 1247 | 0.4297 | 0.8641 |
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- | 0.4294 | 10.9980 | 1372 | 0.4282 | 0.8608 |
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- | 0.3771 | 12.0 | 1497 | 0.4546 | 0.8546 |
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- | 0.4224 | 12.9940 | 1621 | 0.4489 | 0.8625 |
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- | 0.4099 | 13.9960 | 1746 | 0.4411 | 0.8625 |
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- | 0.3759 | 14.9980 | 1871 | 0.4317 | 0.8653 |
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- | 0.3692 | 16.0 | 1996 | 0.4304 | 0.8630 |
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- | 0.364 | 16.9940 | 2120 | 0.4330 | 0.8664 |
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- | 0.3636 | 17.9960 | 2245 | 0.4250 | 0.8681 |
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- | 0.3396 | 18.9980 | 2370 | 0.4275 | 0.8675 |
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- | 0.3057 | 19.8798 | 2480 | 0.4261 | 0.8703 |
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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- - Transformers 4.40.1
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- - Pytorch 2.1.1+cu121
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  - Datasets 2.19.1
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- - Tokenizers 0.19.1
 
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  license: apache-2.0
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  base_model: facebook/convnextv2-tiny-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-tiny-1k-224-finetuned-galaxy10-decals
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  results: []
 
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  # convnextv2-tiny-1k-224-finetuned-galaxy10-decals
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+ This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.4343
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+ - Accuracy: 0.8664
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+ - Precision: 0.8648
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+ - Recall: 0.8664
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+ - F1: 0.8649
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  ## Model description
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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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+ | 1.8139 | 0.99 | 62 | 1.6803 | 0.4628 | 0.4589 | 0.4628 | 0.3836 |
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+ | 1.0894 | 2.0 | 125 | 0.9304 | 0.6984 | 0.6965 | 0.6984 | 0.6800 |
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+ | 0.8423 | 2.99 | 187 | 0.6630 | 0.7880 | 0.7858 | 0.7880 | 0.7826 |
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+ | 0.6564 | 4.0 | 250 | 0.5769 | 0.8055 | 0.8091 | 0.8055 | 0.7970 |
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+ | 0.5927 | 4.99 | 312 | 0.5283 | 0.8241 | 0.8276 | 0.8241 | 0.8240 |
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+ | 0.5853 | 6.0 | 375 | 0.5106 | 0.8303 | 0.8342 | 0.8303 | 0.8237 |
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+ | 0.5757 | 6.99 | 437 | 0.4490 | 0.8540 | 0.8514 | 0.8540 | 0.8521 |
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+ | 0.5235 | 8.0 | 500 | 0.4651 | 0.8546 | 0.8578 | 0.8546 | 0.8536 |
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+ | 0.5166 | 8.99 | 562 | 0.4501 | 0.8563 | 0.8551 | 0.8563 | 0.8523 |
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+ | 0.486 | 10.0 | 625 | 0.4352 | 0.8647 | 0.8624 | 0.8647 | 0.8626 |
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+ | 0.4882 | 10.99 | 687 | 0.4296 | 0.8613 | 0.8594 | 0.8613 | 0.8597 |
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+ | 0.4426 | 12.0 | 750 | 0.4314 | 0.8579 | 0.8614 | 0.8579 | 0.8566 |
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+ | 0.457 | 12.99 | 812 | 0.4226 | 0.8641 | 0.8642 | 0.8641 | 0.8624 |
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+ | 0.4512 | 14.0 | 875 | 0.4319 | 0.8619 | 0.8653 | 0.8619 | 0.8591 |
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+ | 0.4059 | 14.99 | 937 | 0.4124 | 0.8692 | 0.8675 | 0.8692 | 0.8681 |
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+ | 0.4147 | 16.0 | 1000 | 0.3993 | 0.8732 | 0.8714 | 0.8732 | 0.8715 |
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+ | 0.3721 | 16.99 | 1062 | 0.4116 | 0.8636 | 0.8609 | 0.8636 | 0.8604 |
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+ | 0.3908 | 18.0 | 1125 | 0.4098 | 0.8675 | 0.8663 | 0.8675 | 0.8665 |
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+ | 0.3836 | 18.99 | 1187 | 0.4188 | 0.8670 | 0.8651 | 0.8670 | 0.8651 |
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+ | 0.3716 | 20.0 | 1250 | 0.4172 | 0.8681 | 0.8653 | 0.8681 | 0.8661 |
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+ | 0.3484 | 20.99 | 1312 | 0.4404 | 0.8653 | 0.8649 | 0.8653 | 0.8628 |
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+ | 0.3895 | 22.0 | 1375 | 0.4194 | 0.8698 | 0.8689 | 0.8698 | 0.8688 |
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+ | 0.3452 | 22.99 | 1437 | 0.4447 | 0.8630 | 0.8634 | 0.8630 | 0.8621 |
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+ | 0.341 | 24.0 | 1500 | 0.4253 | 0.8720 | 0.8722 | 0.8720 | 0.8712 |
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+ | 0.3481 | 24.99 | 1562 | 0.4325 | 0.8681 | 0.8656 | 0.8681 | 0.8658 |
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+ | 0.3115 | 26.0 | 1625 | 0.4340 | 0.8619 | 0.8609 | 0.8619 | 0.8603 |
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+ | 0.313 | 26.99 | 1687 | 0.4329 | 0.8653 | 0.8644 | 0.8653 | 0.8644 |
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+ | 0.3362 | 28.0 | 1750 | 0.4329 | 0.8653 | 0.8636 | 0.8653 | 0.8639 |
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+ | 0.3056 | 28.99 | 1812 | 0.4342 | 0.8658 | 0.8645 | 0.8658 | 0.8644 |
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+ | 0.3206 | 29.76 | 1860 | 0.4343 | 0.8664 | 0.8648 | 0.8664 | 0.8649 |
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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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