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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_convnext_balanced |
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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: 0.9333333333333333 |
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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_convnext_balanced |
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This model is a fine-tuned version of [facebook/convnext-large-224](https://huggingface.co/facebook/convnext-large-224) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1931 |
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- Accuracy: 0.9333 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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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| 2.0584 | 1.0 | 150 | 1.9386 | 0.6 | |
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| 0.7729 | 2.0 | 300 | 0.6873 | 0.8733 | |
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| 0.4394 | 3.0 | 450 | 0.4321 | 0.89 | |
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| 0.3337 | 4.0 | 600 | 0.3227 | 0.9 | |
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| 0.2489 | 5.0 | 750 | 0.2320 | 0.9267 | |
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| 0.1998 | 6.0 | 900 | 0.2556 | 0.9233 | |
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| 0.1994 | 7.0 | 1050 | 0.2538 | 0.92 | |
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| 0.1573 | 8.0 | 1200 | 0.2224 | 0.9333 | |
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| 0.143 | 9.0 | 1350 | 0.1495 | 0.96 | |
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| 0.0686 | 10.0 | 1500 | 0.1931 | 0.9333 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 2.0.0 |
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- Datasets 2.11.0 |
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- Tokenizers 0.11.0 |
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