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--- |
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base_model: openai/clip-vit-base-patch32 |
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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: ktp-not-ktp-clip |
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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: validation |
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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: 0.989010989010989 |
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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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# ktp-not-ktp-clip |
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This model is a fine-tuned version of [openai/clip-vit-base-patch32](https://huggingface.co/openai/clip-vit-base-patch32) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1267 |
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- Accuracy: 0.9890 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 25 |
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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 | 1.0 | 7 | 0.5809 | 0.6374 | |
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| No log | 2.0 | 14 | 1.3401 | 0.6703 | |
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| 0.5558 | 3.0 | 21 | 0.6458 | 0.7692 | |
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| 0.5558 | 4.0 | 28 | 0.3785 | 0.8681 | |
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| 0.1701 | 5.0 | 35 | 0.3004 | 0.9451 | |
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| 0.1701 | 6.0 | 42 | 0.2204 | 0.9560 | |
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| 0.142 | 7.0 | 49 | 0.1483 | 0.9341 | |
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| 0.142 | 8.0 | 56 | 0.1386 | 0.9670 | |
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| 0.1002 | 9.0 | 63 | 0.7714 | 0.8681 | |
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| 0.1002 | 10.0 | 70 | 0.2285 | 0.9341 | |
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| 0.0956 | 11.0 | 77 | 0.1162 | 0.9780 | |
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| 0.0956 | 12.0 | 84 | 0.1104 | 0.9780 | |
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| 0.0004 | 13.0 | 91 | 0.1722 | 0.9780 | |
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| 0.0004 | 14.0 | 98 | 0.2109 | 0.9780 | |
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| 0.0209 | 15.0 | 105 | 0.3321 | 0.9560 | |
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| 0.0209 | 16.0 | 112 | 0.0785 | 0.9780 | |
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| 0.0209 | 17.0 | 119 | 0.1525 | 0.9670 | |
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| 0.0014 | 18.0 | 126 | 0.1436 | 0.9670 | |
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| 0.0014 | 19.0 | 133 | 0.2278 | 0.9670 | |
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| 0.0002 | 20.0 | 140 | 0.3035 | 0.9560 | |
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| 0.0002 | 21.0 | 147 | 0.1239 | 0.9780 | |
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| 0.001 | 22.0 | 154 | 0.1211 | 0.9890 | |
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| 0.001 | 23.0 | 161 | 0.1253 | 0.9890 | |
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| 0.0 | 24.0 | 168 | 0.1265 | 0.9890 | |
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| 0.0 | 25.0 | 175 | 0.1267 | 0.9890 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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