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README.md
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: plant-seedlings-model
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results:
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- task:
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name: Image Classification
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type: image-classification
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dataset:
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name: imagefolder
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type: imagefolder
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config: default
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split: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.954140127388535
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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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# plant-seedlings-model
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2858
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- Accuracy: 0.9541
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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: 0.0002
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 20
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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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| 1.2496 | 1.27 | 500 | 1.2172 | 0.5637 |
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| 0.7542 | 2.54 | 1000 | 0.8994 | 0.6898 |
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| 0.6158 | 3.82 | 1500 | 0.6794 | 0.7720 |
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| 0.4306 | 5.09 | 2000 | 0.4715 | 0.8331 |
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| 0.3066 | 6.36 | 2500 | 0.4127 | 0.8567 |
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| 0.2851 | 7.63 | 3000 | 0.3460 | 0.8803 |
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| 0.3096 | 8.91 | 3500 | 0.2714 | 0.9019 |
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| 0.1086 | 10.18 | 4000 | 0.2760 | 0.9268 |
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| 0.1209 | 11.45 | 4500 | 0.2881 | 0.9229 |
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| 0.1036 | 12.72 | 5000 | 0.2566 | 0.9357 |
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| 0.0716 | 13.99 | 5500 | 0.2792 | 0.9382 |
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| 0.0168 | 15.27 | 6000 | 0.2604 | 0.9376 |
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| 0.0004 | 16.54 | 6500 | 0.3676 | 0.9363 |
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| 0.0017 | 17.81 | 7000 | 0.2969 | 0.9529 |
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| 0.0005 | 19.08 | 7500 | 0.2858 | 0.9541 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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