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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: dima806/facial_emotions_image_detection |
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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: image_classification2 |
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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: 0.66875 |
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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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# image_classification2 |
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This model is a fine-tuned version of [dima806/facial_emotions_image_detection](https://huggingface.co/dima806/facial_emotions_image_detection) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.9519 |
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- Accuracy: 0.6687 |
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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: 2 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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: 8 |
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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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| 1.8187 | 1.0 | 80 | 1.7527 | 0.4813 | |
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| 1.52 | 2.0 | 160 | 1.3596 | 0.6312 | |
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| 1.4072 | 3.0 | 240 | 1.2119 | 0.5875 | |
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| 1.0868 | 4.0 | 320 | 1.0981 | 0.625 | |
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| 0.9286 | 5.0 | 400 | 1.0133 | 0.6625 | |
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| 0.9353 | 6.0 | 480 | 0.9711 | 0.625 | |
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| 0.7437 | 7.0 | 560 | 0.9389 | 0.6562 | |
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| 0.6774 | 8.0 | 640 | 0.9519 | 0.6687 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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