|
|
--- |
|
|
library_name: transformers |
|
|
license: apache-2.0 |
|
|
base_model: microsoft/beit-base-patch16-224 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: beit-base-patch16-224_rice-leaf-disease-augmented-v2_tl |
|
|
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. --> |
|
|
|
|
|
# beit-base-patch16-224_rice-leaf-disease-augmented-v2_tl |
|
|
|
|
|
This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.4947 |
|
|
- Accuracy: 0.8512 |
|
|
|
|
|
## 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: 128 |
|
|
- eval_batch_size: 128 |
|
|
- 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_ratio: 0.1 |
|
|
- num_epochs: 20 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
|
| 2.0747 | 1.0 | 63 | 1.7043 | 0.4435 | |
|
|
| 1.3282 | 2.0 | 126 | 1.0444 | 0.6845 | |
|
|
| 0.8626 | 3.0 | 189 | 0.7962 | 0.7470 | |
|
|
| 0.6929 | 4.0 | 252 | 0.6883 | 0.8125 | |
|
|
| 0.5935 | 5.0 | 315 | 0.6247 | 0.8214 | |
|
|
| 0.5427 | 6.0 | 378 | 0.5926 | 0.8244 | |
|
|
| 0.5002 | 7.0 | 441 | 0.5735 | 0.8452 | |
|
|
| 0.4704 | 8.0 | 504 | 0.5520 | 0.8482 | |
|
|
| 0.4521 | 9.0 | 567 | 0.5330 | 0.8363 | |
|
|
| 0.4311 | 10.0 | 630 | 0.5249 | 0.8512 | |
|
|
| 0.4096 | 11.0 | 693 | 0.5185 | 0.8512 | |
|
|
| 0.3999 | 12.0 | 756 | 0.5112 | 0.8542 | |
|
|
| 0.3918 | 13.0 | 819 | 0.5042 | 0.8512 | |
|
|
| 0.3862 | 14.0 | 882 | 0.4984 | 0.8542 | |
|
|
| 0.3784 | 15.0 | 945 | 0.4985 | 0.8512 | |
|
|
| 0.3733 | 16.0 | 1008 | 0.4967 | 0.8512 | |
|
|
| 0.3763 | 17.0 | 1071 | 0.4947 | 0.8512 | |
|
|
| 0.3736 | 18.0 | 1134 | 0.4949 | 0.8512 | |
|
|
| 0.3718 | 19.0 | 1197 | 0.4948 | 0.8512 | |
|
|
| 0.3722 | 20.0 | 1260 | 0.4947 | 0.8512 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.48.3 |
|
|
- Pytorch 2.5.1+cu124 |
|
|
- Datasets 3.3.2 |
|
|
- Tokenizers 0.21.0 |
|
|
|
