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library_name: transformers
license: apache-2.0
base_model: facebook/convnextv2-base-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnextv2-base-1k-224_rice-leaf-disease-augmented-v4_v5_pft
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. -->
# convnextv2-base-1k-224_rice-leaf-disease-augmented-v4_v5_pft
This model is a fine-tuned version of [facebook/convnextv2-base-1k-224](https://huggingface.co/facebook/convnextv2-base-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6774
- Accuracy: 0.7819
## 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: 0.0003
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 256
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 2.0691 | 0.5 | 64 | 2.0083 | 0.3523 |
| 1.9566 | 1.0 | 128 | 1.8732 | 0.5201 |
| 1.7715 | 1.5 | 192 | 1.6903 | 0.5638 |
| 1.5752 | 2.0 | 256 | 1.5040 | 0.6074 |
| 1.4088 | 2.5 | 320 | 1.3569 | 0.6208 |
| 1.2927 | 3.0 | 384 | 1.2600 | 0.6309 |
| 1.2173 | 3.5 | 448 | 1.1948 | 0.6577 |
| 1.1515 | 4.0 | 512 | 1.1464 | 0.6644 |
| 1.1183 | 4.5 | 576 | 1.1160 | 0.6711 |
| 1.0893 | 5.0 | 640 | 1.1001 | 0.6879 |
| 1.0792 | 5.5 | 704 | 1.0898 | 0.6913 |
| 1.0627 | 6.0 | 768 | 1.0831 | 0.6846 |
| 1.0714 | 6.5 | 832 | 1.0817 | 0.6846 |
| 1.0459 | 7.0 | 896 | 1.0483 | 0.6913 |
| 1.0282 | 7.5 | 960 | 1.0047 | 0.6980 |
| 0.9605 | 8.0 | 1024 | 0.9774 | 0.7081 |
| 0.9405 | 8.5 | 1088 | 0.9489 | 0.7114 |
| 0.9316 | 9.0 | 1152 | 0.9353 | 0.7148 |
| 0.9174 | 9.5 | 1216 | 0.9208 | 0.7181 |
| 0.8924 | 10.0 | 1280 | 0.9137 | 0.7215 |
| 0.9009 | 10.5 | 1344 | 0.9101 | 0.7282 |
| 0.8844 | 11.0 | 1408 | 0.9092 | 0.7248 |
| 0.8873 | 11.5 | 1472 | 0.9076 | 0.7215 |
| 0.8751 | 12.0 | 1536 | 0.8721 | 0.7383 |
| 0.8553 | 12.5 | 1600 | 0.8617 | 0.7248 |
| 0.8265 | 13.0 | 1664 | 0.8428 | 0.7416 |
| 0.8133 | 13.5 | 1728 | 0.8302 | 0.7416 |
| 0.808 | 14.0 | 1792 | 0.8232 | 0.7483 |
| 0.7915 | 14.5 | 1856 | 0.8187 | 0.7450 |
| 0.7975 | 15.0 | 1920 | 0.8157 | 0.7450 |
| 0.7765 | 15.5 | 1984 | 0.8143 | 0.7450 |
| 0.8017 | 16.0 | 2048 | 0.8142 | 0.7450 |
| 0.793 | 16.5 | 2112 | 0.7970 | 0.7584 |
| 0.7567 | 17.0 | 2176 | 0.7901 | 0.7550 |
| 0.7576 | 17.5 | 2240 | 0.7785 | 0.7483 |
| 0.7377 | 18.0 | 2304 | 0.7651 | 0.7651 |
| 0.7311 | 18.5 | 2368 | 0.7588 | 0.7651 |
| 0.7276 | 19.0 | 2432 | 0.7566 | 0.7651 |
| 0.7237 | 19.5 | 2496 | 0.7567 | 0.7651 |
| 0.7171 | 20.0 | 2560 | 0.7534 | 0.7685 |
| 0.7158 | 20.5 | 2624 | 0.7529 | 0.7685 |
| 0.7188 | 21.0 | 2688 | 0.7486 | 0.7651 |
| 0.7112 | 21.5 | 2752 | 0.7340 | 0.7752 |
| 0.6912 | 22.0 | 2816 | 0.7297 | 0.7752 |
| 0.6784 | 22.5 | 2880 | 0.7229 | 0.7785 |
| 0.6868 | 23.0 | 2944 | 0.7152 | 0.7752 |
| 0.6701 | 23.5 | 3008 | 0.7132 | 0.7819 |
| 0.6718 | 24.0 | 3072 | 0.7111 | 0.7752 |
| 0.671 | 24.5 | 3136 | 0.7105 | 0.7785 |
| 0.6609 | 25.0 | 3200 | 0.7097 | 0.7785 |
| 0.6722 | 25.5 | 3264 | 0.7066 | 0.7785 |
| 0.6526 | 26.0 | 3328 | 0.6959 | 0.7785 |
| 0.6448 | 26.5 | 3392 | 0.6920 | 0.7919 |
| 0.6493 | 27.0 | 3456 | 0.6903 | 0.7785 |
| 0.6394 | 27.5 | 3520 | 0.6816 | 0.7785 |
| 0.6274 | 28.0 | 3584 | 0.6819 | 0.7819 |
| 0.6198 | 28.5 | 3648 | 0.6784 | 0.7819 |
| 0.632 | 29.0 | 3712 | 0.6778 | 0.7819 |
| 0.634 | 29.5 | 3776 | 0.6776 | 0.7819 |
| 0.612 | 30.0 | 3840 | 0.6774 | 0.7819 |
### Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.1
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