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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: dennisjooo/Birds-Classifier-EfficientNetB2 |
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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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- f1 |
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- precision |
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- recall |
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- accuracy |
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model-index: |
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- name: train_checkpoints2 |
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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: validation |
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args: default |
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metrics: |
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- name: F1 |
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type: f1 |
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value: 0.8685894687564659 |
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- name: Precision |
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type: precision |
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value: 0.8781544844044844 |
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- name: Recall |
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type: recall |
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value: 0.8634882138558609 |
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- name: Accuracy |
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type: accuracy |
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value: 0.8686131386861314 |
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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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# train_checkpoints2 |
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This model is a fine-tuned version of [dennisjooo/Birds-Classifier-EfficientNetB2](https://huggingface.co/dennisjooo/Birds-Classifier-EfficientNetB2) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4826 |
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- F1: 0.8686 |
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- Precision: 0.8782 |
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- Recall: 0.8635 |
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- Accuracy: 0.8686 |
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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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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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 | F1 | Precision | Recall | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|:--------:| |
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| 0.1145 | 1.0 | 15 | 0.5836 | 0.8608 | 0.8776 | 0.8520 | 0.8613 | |
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| 0.129 | 2.0 | 30 | 0.8019 | 0.8322 | 0.8634 | 0.8192 | 0.8358 | |
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| 0.2085 | 3.0 | 45 | 0.7550 | 0.8083 | 0.8355 | 0.8042 | 0.8212 | |
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| 0.1722 | 4.0 | 60 | 0.7524 | 0.8298 | 0.8422 | 0.8357 | 0.8394 | |
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| 0.19 | 5.0 | 75 | 0.5542 | 0.8743 | 0.8910 | 0.8679 | 0.8723 | |
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| 0.1612 | 6.0 | 90 | 0.8325 | 0.8114 | 0.8410 | 0.8063 | 0.8066 | |
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| 0.2009 | 7.0 | 105 | 0.4425 | 0.8900 | 0.8904 | 0.8911 | 0.8942 | |
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| 0.209 | 8.0 | 120 | 0.6705 | 0.8126 | 0.8482 | 0.8074 | 0.8358 | |
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| 0.2188 | 9.0 | 135 | 0.5906 | 0.8387 | 0.8551 | 0.8350 | 0.8467 | |
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| 0.1962 | 10.0 | 150 | 0.4826 | 0.8686 | 0.8782 | 0.8635 | 0.8686 | |
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### Framework versions |
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- Transformers 4.49.0 |
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- Pytorch 2.6.0+cu124 |
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- Datasets 3.3.2 |
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- Tokenizers 0.21.0 |
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