File size: 2,440 Bytes
e53040e ba1c9a4 e53040e 2c96cd0 ba1c9a4 e53040e 2c96cd0 e53040e ba1c9a4 f80ba1b ba1c9a4 e53040e 70d08ea e53040e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 |
---
library_name: transformers
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: dinov2-base_rice-leaf-disease-augmented_fft_012825
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. -->
# dinov2-base_rice-leaf-disease-augmented_fft_012825
This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0125
- Accuracy: 0.9965
## 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: 5e-05
- 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: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
### Training results
| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 0.8384 | 1.0 | 250 | 0.931 | 0.2042 |
| 0.1037 | 2.0 | 500 | 0.96 | 0.1290 |
| 0.0574 | 3.0 | 750 | 0.977 | 0.0657 |
| 0.0255 | 4.0 | 1000 | 0.985 | 0.0527 |
| 0.0096 | 5.0 | 1250 | 0.988 | 0.0374 |
| 0.0052 | 6.0 | 1500 | 0.997 | 0.0128 |
| 0.0018 | 7.0 | 1750 | 0.9945 | 0.0131 |
| 0.0027 | 8.0 | 2000 | 0.997 | 0.0122 |
| 0.0004 | 9.0 | 2250 | 0.997 | 0.0153 |
| 0.0013 | 10.0 | 2500 | 0.997 | 0.0128 |
| 0.0004 | 11.0 | 2750 | 0.9965 | 0.0147 |
| 0.0004 | 12.0 | 3000 | 0.997 | 0.0155 |
| 0.0003 | 13.0 | 3250 | 0.9955 | 0.0118 |
| 0.0004 | 14.0 | 3500 | 0.9955 | 0.0123 |
| 0.0003 | 15.0 | 3750 | 0.9965 | 0.0125 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|