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---
license: apache-2.0
tags:
- image-classification
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: exper1_mesum5
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. -->
# exper1_mesum5
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 sudo-s/herbier_mesuem5 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6401
- Accuracy: 0.8278
## 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: 0.0002
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.9352 | 0.23 | 100 | 3.8550 | 0.1959 |
| 3.1536 | 0.47 | 200 | 3.1755 | 0.2888 |
| 2.6937 | 0.7 | 300 | 2.6332 | 0.4272 |
| 2.3748 | 0.93 | 400 | 2.2833 | 0.4970 |
| 1.5575 | 1.16 | 500 | 1.8712 | 0.5888 |
| 1.4063 | 1.4 | 600 | 1.6048 | 0.6314 |
| 1.1841 | 1.63 | 700 | 1.4109 | 0.6621 |
| 1.0857 | 1.86 | 800 | 1.1832 | 0.7112 |
| 0.582 | 2.09 | 900 | 1.0371 | 0.7479 |
| 0.5971 | 2.33 | 1000 | 0.9839 | 0.7462 |
| 0.4617 | 2.56 | 1100 | 0.9233 | 0.7657 |
| 0.4621 | 2.79 | 1200 | 0.8417 | 0.7828 |
| 0.2128 | 3.02 | 1300 | 0.7644 | 0.7970 |
| 0.1883 | 3.26 | 1400 | 0.7001 | 0.8183 |
| 0.1501 | 3.49 | 1500 | 0.6826 | 0.8201 |
| 0.1626 | 3.72 | 1600 | 0.6568 | 0.8254 |
| 0.1053 | 3.95 | 1700 | 0.6401 | 0.8278 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu113
- Datasets 2.3.2
- Tokenizers 0.12.1
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