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--- |
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license: apache-2.0 |
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base_model: NekoFi/portrait_cosu_exp4 |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: portrait_cosu_exp5 |
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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: 0.9583333333333334 |
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- name: Precision |
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type: precision |
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value: 0.9581730769230768 |
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- name: Recall |
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type: recall |
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value: 0.9583333333333334 |
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- name: F1 |
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type: f1 |
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value: 0.9580274686242009 |
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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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# portrait_cosu_exp5 |
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This model is a fine-tuned version of [NekoFi/portrait_cosu_exp4](https://huggingface.co/NekoFi/portrait_cosu_exp4) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1603 |
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- Accuracy: 0.9583 |
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- Precision: 0.9582 |
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- Recall: 0.9583 |
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- F1: 0.9580 |
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- Confusion Matrix: [[50, 1], [2, 19]] |
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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: 4 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Confusion Matrix | |
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|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------------------:| |
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| 0.3966 | 0.9756 | 10 | 0.3024 | 0.8611 | 0.8695 | 0.8611 | 0.8498 | [[50, 1], [9, 12]] | |
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| 0.3486 | 1.9512 | 20 | 0.3286 | 0.8333 | 0.8458 | 0.8333 | 0.8147 | [[50, 1], [11, 10]] | |
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| 0.2347 | 2.9268 | 30 | 0.1769 | 0.9444 | 0.9446 | 0.9444 | 0.9436 | [[50, 1], [3, 18]] | |
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| 0.2039 | 3.9024 | 40 | 0.1603 | 0.9583 | 0.9582 | 0.9583 | 0.9580 | [[50, 1], [2, 19]] | |
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### Framework versions |
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- Transformers 4.41.1 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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