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habibi26
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ktp-kk-crop

Image Classification
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clip
Generated from Trainer
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  1. README.md +101 -0
  2. model.safetensors +1 -1
  3. runs/Jul09_04-46-11_2f6ca34d0b80/events.out.tfevents.1720500406.2f6ca34d0b80.34.0 +2 -2
README.md ADDED
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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-kk-crop
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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: 0.945054945054945
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+ ---
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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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+
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+ # ktp-kk-crop
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+
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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: 0.2528
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+ - Accuracy: 0.9451
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:----:|:---------------:|:--------:|
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+ | No log | 0.9655 | 7 | 0.5985 | 0.6154 |
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+ | No log | 1.9310 | 14 | 0.1681 | 0.9341 |
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+ | 0.4711 | 2.8966 | 21 | 0.2271 | 0.9011 |
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+ | 0.4711 | 4.0 | 29 | 0.8009 | 0.7473 |
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+ | 0.3768 | 4.9655 | 36 | 0.1365 | 0.9560 |
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+ | 0.3768 | 5.9310 | 43 | 0.1176 | 0.9780 |
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+ | 0.069 | 6.8966 | 50 | 0.0880 | 0.9890 |
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+ | 0.069 | 8.0 | 58 | 0.6839 | 0.9011 |
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+ | 0.0212 | 8.9655 | 65 | 0.3376 | 0.9451 |
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+ | 0.0212 | 9.9310 | 72 | 0.2240 | 0.9670 |
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+ | 0.0201 | 10.8966 | 79 | 0.5612 | 0.9341 |
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+ | 0.0201 | 12.0 | 87 | 0.2688 | 0.9560 |
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+ | 0.0039 | 12.9655 | 94 | 0.1710 | 0.9780 |
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+ | 0.0039 | 13.9310 | 101 | 0.3437 | 0.9560 |
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+ | 0.0293 | 14.8966 | 108 | 0.2446 | 0.9670 |
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+ | 0.0293 | 16.0 | 116 | 0.1507 | 0.9780 |
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+ | 0.0009 | 16.9655 | 123 | 0.2032 | 0.9670 |
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+ | 0.0009 | 17.9310 | 130 | 0.2481 | 0.9451 |
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+ | 0.0 | 18.8966 | 137 | 0.2608 | 0.9451 |
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+ | 0.0 | 20.0 | 145 | 0.2611 | 0.9451 |
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+ | 0.0 | 20.9655 | 152 | 0.2579 | 0.9451 |
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+ | 0.0 | 21.9310 | 159 | 0.2554 | 0.9451 |
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+ | 0.0 | 22.8966 | 166 | 0.2536 | 0.9451 |
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+ | 0.0 | 24.0 | 174 | 0.2528 | 0.9451 |
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+ | 0.0 | 24.1379 | 175 | 0.2528 | 0.9451 |
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+
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+
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+ ### Framework versions
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+
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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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