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README.md
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This model is a fine-tuned version of [tigeryi/imagenet1k](https://huggingface.co/tigeryi/imagenet1k) on an unknown dataset.
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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: 0.
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 1
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- num_epochs:
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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 4.40.
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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This model is a fine-tuned version of [tigeryi/imagenet1k](https://huggingface.co/tigeryi/imagenet1k) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0970
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- Accuracy: 0.99
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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: 0.0001
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 1
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- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- num_epochs: 2
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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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| 0.8141 | 1.0 | 25 | 0.2320 | 0.95 |
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| 0.7293 | 2.0 | 50 | 0.0970 | 0.99 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.2.1+cu121
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- Datasets 2.19.0
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- Tokenizers 0.19.1
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