End of training
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- config.json +1 -1
- model.safetensors +1 -1
README.md
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---
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base_model: nateraw/vit-age-classifier
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datasets:
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- imagefolder
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library_name: transformers
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metrics:
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- accuracy
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tags:
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- generated_from_trainer
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model-index:
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- name: results
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results:
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- task:
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type: image-classification
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name: Image Classification
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dataset:
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name: imagefolder
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type: imagefolder
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split: train
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args: default
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metrics:
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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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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.
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.
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### Framework versions
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---
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library_name: transformers
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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: results
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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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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: 0.5
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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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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: 1.7301
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- Accuracy: 0.5
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 2.0108 | 1.0 | 40 | 1.9813 | 0.325 |
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| 1.7144 | 2.0 | 80 | 1.8097 | 0.45 |
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| 1.5272 | 3.0 | 120 | 1.7301 | 0.5 |
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### Framework versions
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config.json
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{
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"_name_or_path": "
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"architectures": [
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"ViTForImageClassification"
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],
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{
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"_name_or_path": "nateraw/vit-age-classifier",
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"architectures": [
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"ViTForImageClassification"
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],
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model.safetensors
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