Model save
Browse files- README.md +38 -38
- config.json +9 -9
- model.safetensors +1 -1
- preprocessor_config.json +8 -21
- runs/Apr18_08-26-03_0516a0f7e8d9/events.out.tfevents.1713428782.0516a0f7e8d9.4214.0 +3 -0
- training_args.bin +2 -2
README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Accuracy: 0.
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size:
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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:
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- mixed_precision_training: Native AMP
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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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### Framework versions
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- Transformers 4.
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- Pytorch 2.1
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7495238095238095
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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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9816
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- Accuracy: 0.7495
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 0.0001
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- train_batch_size: 16
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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: 5
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- mixed_precision_training: Native AMP
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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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| 1.4818 | 0.16 | 100 | 1.2573 | 0.7219 |
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| 1.0598 | 0.32 | 200 | 0.9673 | 0.7419 |
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| 0.9126 | 0.48 | 300 | 0.8612 | 0.7514 |
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| 0.6733 | 0.64 | 400 | 0.9162 | 0.7038 |
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| 0.7302 | 0.8 | 500 | 0.9483 | 0.7124 |
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| 0.7024 | 0.96 | 600 | 0.7318 | 0.7752 |
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| 0.5469 | 1.11 | 700 | 1.0155 | 0.6990 |
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| 0.4757 | 1.27 | 800 | 0.8299 | 0.7438 |
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| 0.4618 | 1.43 | 900 | 0.7697 | 0.7648 |
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| 0.5045 | 1.59 | 1000 | 0.9454 | 0.7152 |
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| 0.4229 | 1.75 | 1100 | 0.7776 | 0.7629 |
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| 0.3894 | 1.91 | 1200 | 0.8798 | 0.7495 |
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| 0.3432 | 2.07 | 1300 | 0.8088 | 0.7590 |
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| 0.3212 | 2.23 | 1400 | 0.7810 | 0.7733 |
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| 0.3043 | 2.39 | 1500 | 1.0076 | 0.7295 |
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| 0.255 | 2.55 | 1600 | 0.8672 | 0.7590 |
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| 0.2834 | 2.71 | 1700 | 0.9165 | 0.7438 |
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| 0.341 | 2.87 | 1800 | 0.7474 | 0.7838 |
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| 0.1858 | 3.03 | 1900 | 1.0221 | 0.7229 |
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| 0.2463 | 3.18 | 2000 | 0.8464 | 0.7829 |
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| 0.2661 | 3.34 | 2100 | 0.9434 | 0.7476 |
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| 0.2367 | 3.5 | 2200 | 0.9285 | 0.76 |
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| 0.2299 | 3.66 | 2300 | 0.9777 | 0.7486 |
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| 0.221 | 3.82 | 2400 | 0.9455 | 0.7533 |
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| 0.2799 | 3.98 | 2500 | 1.0371 | 0.74 |
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| 0.1185 | 4.14 | 2600 | 1.0378 | 0.7390 |
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| 0.1405 | 4.3 | 2700 | 1.0870 | 0.7352 |
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| 0.263 | 4.46 | 2800 | 1.1081 | 0.7276 |
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| 0.254 | 4.62 | 2900 | 1.0279 | 0.7381 |
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| 0.158 | 4.78 | 3000 | 0.9646 | 0.7514 |
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| 0.1496 | 4.94 | 3100 | 0.9816 | 0.7495 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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config.json
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"label2id": {
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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}
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"\u09b9\u09be\u0981\u099f\u09be": "9"
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"problem_type": "single_label_classification",
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"qkv_bias": true,
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"torch_dtype": "float32",
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"transformers_version": "4.38.2"
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}
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model.safetensors
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preprocessor_config.json
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{
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"images",
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"do_normalize": true,
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"size": {
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"do_normalize": true,
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"do_resize": true,
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runs/Apr18_08-26-03_0516a0f7e8d9/events.out.tfevents.1713428782.0516a0f7e8d9.4214.0
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training_args.bin
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