End of training
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- pytorch_model.bin +1 -1
README.md
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@@ -4,7 +4,7 @@ base_model: google/vit-base-patch16-224-in21k
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tags:
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- generated_from_trainer
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datasets:
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metrics:
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- accuracy
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model-index:
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name: Image Classification
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type: image-classification
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dataset:
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name:
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type:
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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.
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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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# image_classification
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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
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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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 |
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| No log | 2.0 |
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| No log | 3.0 |
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### Framework versions
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- Transformers 4.33.
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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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: 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: 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: 0.5875
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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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# image_classification
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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: 1.2378
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- Accuracy: 0.5875
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 2e-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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- 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: 20
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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 | 40 | 2.0656 | 0.125 |
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| No log | 2.0 | 80 | 2.0558 | 0.1938 |
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| No log | 3.0 | 120 | 2.0177 | 0.2375 |
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| No log | 4.0 | 160 | 1.9156 | 0.3438 |
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| No log | 5.0 | 200 | 1.7849 | 0.3063 |
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| No log | 6.0 | 240 | 1.6961 | 0.3187 |
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| No log | 7.0 | 280 | 1.6026 | 0.3937 |
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| No log | 8.0 | 320 | 1.5455 | 0.3688 |
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| No log | 9.0 | 360 | 1.4723 | 0.4562 |
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| No log | 10.0 | 400 | 1.3931 | 0.5 |
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| No log | 11.0 | 440 | 1.4418 | 0.4375 |
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| No log | 12.0 | 480 | 1.3306 | 0.4437 |
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| 1.5855 | 13.0 | 520 | 1.2437 | 0.575 |
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| 1.5855 | 14.0 | 560 | 1.3712 | 0.4875 |
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| 1.5855 | 15.0 | 600 | 1.2102 | 0.55 |
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| 1.5855 | 16.0 | 640 | 1.3217 | 0.5188 |
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| 1.5855 | 17.0 | 680 | 1.3656 | 0.4938 |
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| 1.5855 | 18.0 | 720 | 1.3261 | 0.525 |
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| 1.5855 | 19.0 | 760 | 1.5611 | 0.4625 |
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| 1.5855 | 20.0 | 800 | 1.4503 | 0.5125 |
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### Framework versions
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- Transformers 4.33.2
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- Pytorch 2.0.1+cu118
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- Datasets 2.14.5
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- Tokenizers 0.13.3
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pytorch_model.bin
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