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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-384 |
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tags: |
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- generated_from_trainer |
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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: 10-vit-base-patch16-384-finetuned-spiderTraining20-500 |
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results: [] |
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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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# 10-vit-base-patch16-384-finetuned-spiderTraining20-500 |
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This model is a fine-tuned version of [google/vit-base-patch16-384](https://huggingface.co/google/vit-base-patch16-384) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3427 |
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- Accuracy: 0.9029 |
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- Precision: 0.9012 |
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- Recall: 0.9032 |
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- F1: 0.9009 |
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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: 0.0005 |
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- train_batch_size: 25 |
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- eval_batch_size: 25 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 100 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| 0.6925 | 1.0 | 80 | 0.6605 | 0.7938 | 0.8012 | 0.7887 | 0.7869 | |
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| 0.5869 | 2.0 | 160 | 0.5574 | 0.8298 | 0.8350 | 0.8254 | 0.8214 | |
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| 0.4858 | 3.0 | 240 | 0.4335 | 0.8689 | 0.8692 | 0.8644 | 0.8644 | |
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| 0.3921 | 4.0 | 320 | 0.4455 | 0.8739 | 0.8737 | 0.8722 | 0.8699 | |
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| 0.2915 | 5.0 | 400 | 0.4707 | 0.8629 | 0.8708 | 0.8612 | 0.8571 | |
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| 0.2727 | 6.0 | 480 | 0.4471 | 0.8819 | 0.8795 | 0.8808 | 0.8777 | |
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| 0.216 | 7.0 | 560 | 0.3809 | 0.8899 | 0.8879 | 0.8874 | 0.8862 | |
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| 0.1685 | 8.0 | 640 | 0.3760 | 0.8949 | 0.8938 | 0.8934 | 0.8915 | |
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| 0.1292 | 9.0 | 720 | 0.3427 | 0.9049 | 0.9034 | 0.9032 | 0.9021 | |
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| 0.1321 | 10.0 | 800 | 0.3427 | 0.9029 | 0.9012 | 0.9032 | 0.9009 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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