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---
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Plant_Classification_model_vit-base-patch16-224-in21k
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. -->
# Plant_Classification_model_vit-base-patch16-224-in21k
This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2650
- Accuracy: 0.6667
## 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: 1e-05
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 20
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 65 | 3.2430 | 0.0994 |
| No log | 2.0 | 130 | 3.1265 | 0.3060 |
| No log | 3.0 | 195 | 3.0009 | 0.3743 |
| No log | 4.0 | 260 | 2.8860 | 0.4133 |
| No log | 5.0 | 325 | 2.7848 | 0.4464 |
| No log | 6.0 | 390 | 2.6989 | 0.4951 |
| No log | 7.0 | 455 | 2.6229 | 0.5380 |
| 2.8794 | 8.0 | 520 | 2.5590 | 0.5653 |
| 2.8794 | 9.0 | 585 | 2.5042 | 0.5926 |
| 2.8794 | 10.0 | 650 | 2.4560 | 0.5984 |
| 2.8794 | 11.0 | 715 | 2.4151 | 0.6199 |
| 2.8794 | 12.0 | 780 | 2.3813 | 0.6316 |
| 2.8794 | 13.0 | 845 | 2.3516 | 0.6452 |
| 2.8794 | 14.0 | 910 | 2.3275 | 0.6511 |
| 2.8794 | 15.0 | 975 | 2.3079 | 0.6530 |
| 2.2983 | 16.0 | 1040 | 2.2919 | 0.6589 |
| 2.2983 | 17.0 | 1105 | 2.2801 | 0.6647 |
| 2.2983 | 18.0 | 1170 | 2.2717 | 0.6667 |
| 2.2983 | 19.0 | 1235 | 2.2667 | 0.6667 |
| 2.2983 | 20.0 | 1300 | 2.2650 | 0.6667 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.0.0
- Datasets 2.15.0
- Tokenizers 0.15.0
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