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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: weeds_hfclass12 |
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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: test |
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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: 0.96 |
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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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# weeds_hfclass12 |
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Model is trained on balanced dataset/ 250 image per class/ .8 .1 .1 split/ 224x224 resized |
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Dataset: https://www.kaggle.com/datasets/vbookshelf/v2-plant-seedlings-dataset |
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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: 0.1257 |
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- Accuracy: 0.96 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 10 |
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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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| 1.6013 | 0.99 | 37 | 0.7579 | 0.8067 | |
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| 0.3887 | 1.99 | 74 | 0.2834 | 0.9033 | |
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| 0.2846 | 2.99 | 111 | 0.2767 | 0.9 | |
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| 0.2086 | 3.99 | 148 | 0.2642 | 0.9067 | |
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| 0.1664 | 4.99 | 185 | 0.2016 | 0.9333 | |
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| 0.168 | 5.99 | 222 | 0.1498 | 0.9533 | |
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| 0.1159 | 6.99 | 259 | 0.1607 | 0.9533 | |
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| 0.1195 | 7.99 | 296 | 0.1719 | 0.9467 | |
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| 0.1013 | 8.99 | 333 | 0.1442 | 0.9533 | |
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| 0.0939 | 9.99 | 370 | 0.1257 | 0.96 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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