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--- |
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base_model: nateraw/vit-age-classifier |
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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_classification |
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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: 0.34375 |
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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_classification |
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This model is a fine-tuned version of [nateraw/vit-age-classifier](https://huggingface.co/nateraw/vit-age-classifier) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.8469 |
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- Accuracy: 0.3438 |
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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: 1e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 512 |
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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: 0.3 |
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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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| No log | 0.8 | 1 | 1.8452 | 0.3125 | |
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| No log | 1.6 | 2 | 1.8435 | 0.35 | |
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| No log | 2.4 | 3 | 1.8282 | 0.3688 | |
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| No log | 4.0 | 5 | 1.8112 | 0.3563 | |
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| No log | 4.8 | 6 | 1.8180 | 0.3312 | |
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| No log | 5.6 | 7 | 1.8291 | 0.3375 | |
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| No log | 6.4 | 8 | 1.8036 | 0.3563 | |
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| 1.6711 | 8.0 | 10 | 1.8134 | 0.3375 | |
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### Framework versions |
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- Transformers 4.42.4 |
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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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