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--- |
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base_model: d071696/vit-finetune-scrap |
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tags: |
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- image-classification |
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- image-feature-extraction |
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- image-to-text |
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- generated_from_trainer |
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datasets: |
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- arrow |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-finetune-scrap |
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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: d071696/scraps1 |
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type: arrow |
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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: 0.9260450160771704 |
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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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# vit-finetune-scrap |
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This model is a fine-tuned version of [d071696/vit-finetune-scrap](https://huggingface.co/d071696/vit-finetune-scrap) on the d071696/scraps1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3599 |
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- Accuracy: 0.9260 |
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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: 0.0002 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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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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- num_epochs: 4 |
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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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| 0.0021 | 3.22 | 1000 | 0.3599 | 0.9260 | |
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### Framework versions |
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- Transformers 4.39.0 |
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- Pytorch 2.2.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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