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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: timm/efficientformer_l1.snap_dist_in1k |
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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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model-index: |
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- name: efficientformer_l1.snap_dist_in1k_rice-leaf-disease-augmented-v4_v5_fft |
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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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# efficientformer_l1.snap_dist_in1k_rice-leaf-disease-augmented-v4_v5_fft |
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This model is a fine-tuned version of [timm/efficientformer_l1.snap_dist_in1k](https://huggingface.co/timm/efficientformer_l1.snap_dist_in1k) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4269 |
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- Accuracy: 0.9060 |
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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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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine_with_restarts |
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- lr_scheduler_warmup_steps: 256 |
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- num_epochs: 30 |
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- mixed_precision_training: Native AMP |
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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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| 2.0721 | 0.5 | 64 | 2.0503 | 0.1812 | |
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| 1.9705 | 1.0 | 128 | 1.8812 | 0.4128 | |
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| 1.7172 | 1.5 | 192 | 1.5160 | 0.5570 | |
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| 1.3261 | 2.0 | 256 | 1.0740 | 0.6779 | |
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| 0.8641 | 2.5 | 320 | 0.7390 | 0.7718 | |
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| 0.5772 | 3.0 | 384 | 0.5308 | 0.8289 | |
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| 0.3856 | 3.5 | 448 | 0.4667 | 0.8389 | |
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| 0.2981 | 4.0 | 512 | 0.4052 | 0.8523 | |
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| 0.213 | 4.5 | 576 | 0.3778 | 0.8591 | |
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| 0.1795 | 5.0 | 640 | 0.3505 | 0.8792 | |
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| 0.1435 | 5.5 | 704 | 0.3455 | 0.8859 | |
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| 0.1309 | 6.0 | 768 | 0.3440 | 0.8826 | |
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| 0.1243 | 6.5 | 832 | 0.3309 | 0.8893 | |
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| 0.1142 | 7.0 | 896 | 0.3252 | 0.8758 | |
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| 0.0837 | 7.5 | 960 | 0.3259 | 0.8893 | |
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| 0.059 | 8.0 | 1024 | 0.3085 | 0.9060 | |
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| 0.0296 | 8.5 | 1088 | 0.2963 | 0.8960 | |
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| 0.0208 | 9.0 | 1152 | 0.3109 | 0.8993 | |
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| 0.0092 | 9.5 | 1216 | 0.3261 | 0.9027 | |
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| 0.0098 | 10.0 | 1280 | 0.3265 | 0.8960 | |
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| 0.0056 | 10.5 | 1344 | 0.3280 | 0.9027 | |
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| 0.0068 | 11.0 | 1408 | 0.3289 | 0.9060 | |
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| 0.005 | 11.5 | 1472 | 0.3590 | 0.8893 | |
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| 0.0058 | 12.0 | 1536 | 0.3379 | 0.9060 | |
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| 0.0025 | 12.5 | 1600 | 0.3744 | 0.9094 | |
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| 0.0026 | 13.0 | 1664 | 0.3851 | 0.9060 | |
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| 0.0016 | 13.5 | 1728 | 0.3950 | 0.9027 | |
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| 0.0011 | 14.0 | 1792 | 0.3766 | 0.9128 | |
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| 0.0007 | 14.5 | 1856 | 0.3729 | 0.9161 | |
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| 0.0011 | 15.0 | 1920 | 0.3591 | 0.9027 | |
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| 0.0006 | 15.5 | 1984 | 0.3769 | 0.8993 | |
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| 0.0006 | 16.0 | 2048 | 0.3660 | 0.9094 | |
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| 0.0005 | 16.5 | 2112 | 0.3687 | 0.9195 | |
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| 0.0006 | 17.0 | 2176 | 0.3933 | 0.9060 | |
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| 0.0006 | 17.5 | 2240 | 0.3849 | 0.9128 | |
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| 0.0006 | 18.0 | 2304 | 0.4178 | 0.9027 | |
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| 0.0009 | 18.5 | 2368 | 0.4092 | 0.9027 | |
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| 0.0002 | 19.0 | 2432 | 0.4117 | 0.9094 | |
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| 0.0003 | 19.5 | 2496 | 0.4075 | 0.9060 | |
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| 0.0003 | 20.0 | 2560 | 0.4116 | 0.9094 | |
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| 0.0002 | 20.5 | 2624 | 0.3974 | 0.9094 | |
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| 0.0004 | 21.0 | 2688 | 0.4266 | 0.8993 | |
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| 0.0004 | 21.5 | 2752 | 0.4172 | 0.9128 | |
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| 0.0004 | 22.0 | 2816 | 0.4450 | 0.9027 | |
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| 0.0003 | 22.5 | 2880 | 0.4505 | 0.9060 | |
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| 0.0002 | 23.0 | 2944 | 0.4213 | 0.9027 | |
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| 0.0001 | 23.5 | 3008 | 0.4285 | 0.9027 | |
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| 0.0001 | 24.0 | 3072 | 0.4368 | 0.9027 | |
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| 0.0002 | 24.5 | 3136 | 0.4330 | 0.9060 | |
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| 0.0002 | 25.0 | 3200 | 0.4294 | 0.9060 | |
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| 0.0001 | 25.5 | 3264 | 0.4395 | 0.9027 | |
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| 0.0006 | 26.0 | 3328 | 0.4304 | 0.9060 | |
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| 0.0001 | 26.5 | 3392 | 0.4203 | 0.9161 | |
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| 0.0001 | 27.0 | 3456 | 0.4403 | 0.9094 | |
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| 0.0002 | 27.5 | 3520 | 0.4447 | 0.9027 | |
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| 0.0001 | 28.0 | 3584 | 0.4348 | 0.9094 | |
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| 0.0001 | 28.5 | 3648 | 0.4200 | 0.9094 | |
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| 0.0001 | 29.0 | 3712 | 0.4340 | 0.9094 | |
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| 0.0001 | 29.5 | 3776 | 0.4402 | 0.9094 | |
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| 0.0001 | 30.0 | 3840 | 0.4269 | 0.9060 | |
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### Framework versions |
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- Transformers 4.48.3 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.1 |
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