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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_hfclass18 |
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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: 0.7766666666666666 |
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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_hfclass18 |
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Model is trained on balanced dataset/250 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/resnet-152](https://huggingface.co/microsoft/resnet-152) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2397 |
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- Accuracy: 0.7767 |
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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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| 2.4803 | 0.99 | 37 | 2.4724 | 0.1133 | |
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| 2.4464 | 1.99 | 74 | 2.4305 | 0.2967 | |
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| 2.3843 | 2.99 | 111 | 2.3658 | 0.4233 | |
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| 2.3018 | 3.99 | 148 | 2.2287 | 0.5067 | |
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| 2.1075 | 4.99 | 185 | 2.0144 | 0.5967 | |
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| 1.8743 | 5.99 | 222 | 1.7228 | 0.65 | |
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| 1.7114 | 6.99 | 259 | 1.5487 | 0.6833 | |
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| 1.5345 | 7.99 | 296 | 1.3920 | 0.7267 | |
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| 1.4471 | 8.99 | 333 | 1.2914 | 0.7333 | |
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| 1.3994 | 9.99 | 370 | 1.2397 | 0.7767 | |
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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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