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End of training
Browse files- README.md +87 -0
- model.safetensors +1 -1
README.md
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---
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license: apache-2.0
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base_model: facebook/deit-base-patch16-224
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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: hushem_40x_deit_base_n_f3
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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: test
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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: 0.9069767441860465
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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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# hushem_40x_deit_base_n_f3
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This model is a fine-tuned version of [facebook/deit-base-patch16-224](https://huggingface.co/facebook/deit-base-patch16-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4024
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- Accuracy: 0.9070
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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: 10
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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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| 0.1057 | 1.0 | 108 | 0.5226 | 0.8372 |
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| 0.0057 | 2.0 | 217 | 0.4792 | 0.9070 |
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| 0.0066 | 3.0 | 325 | 0.2934 | 0.9302 |
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| 0.0008 | 4.0 | 434 | 0.2441 | 0.9535 |
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| 0.0001 | 5.0 | 542 | 0.3621 | 0.9070 |
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| 0.0 | 6.0 | 651 | 0.3864 | 0.9070 |
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| 0.0 | 7.0 | 759 | 0.3930 | 0.9070 |
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| 0.0 | 8.0 | 868 | 0.3984 | 0.9070 |
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| 0.0 | 9.0 | 976 | 0.4017 | 0.9070 |
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| 0.0 | 9.95 | 1080 | 0.4024 | 0.9070 |
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### Framework versions
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- Transformers 4.35.0
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- Pytorch 2.1.0+cu118
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- Datasets 2.14.6
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- Tokenizers 0.14.1
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model.safetensors
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