Model save
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README.md
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---
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license: mit
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base_model: shi-labs/nat-mini-in1k-224
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tags:
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- generated_from_trainer
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datasets:
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- image_folder
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metrics:
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- accuracy
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- f1
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model-index:
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- name: nat-mini-in1k-224-finetuned-breakhis
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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: image_folder
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type: image_folder
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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: 0.9669421487603306
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- name: F1
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type: f1
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value: 0.9612429172231991
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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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# nat-mini-in1k-224-finetuned-breakhis
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This model is a fine-tuned version of [shi-labs/nat-mini-in1k-224](https://huggingface.co/shi-labs/nat-mini-in1k-224) on the image_folder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0983
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- Accuracy: 0.9669
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- F1: 0.9612
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- Roc Auc: 0.9648
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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: 32
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- eval_batch_size: 32
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 128
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Roc Auc |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:-------:|
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| 0.3247 | 0.99 | 59 | 0.2084 | 0.9157 | 0.8968 | 0.8836 |
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| 0.1338 | 2.0 | 119 | 0.1686 | 0.9355 | 0.9266 | 0.9437 |
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| 0.1078 | 2.99 | 178 | 0.0986 | 0.9694 | 0.9636 | 0.9597 |
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| 0.0795 | 4.0 | 238 | 0.0957 | 0.9719 | 0.9668 | 0.9660 |
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| 0.0522 | 4.96 | 295 | 0.0983 | 0.9669 | 0.9612 | 0.9648 |
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### Framework versions
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- Transformers 4.38.1
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- Pytorch 2.1.2
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- Datasets 2.1.0
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- Tokenizers 0.15.2
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runs/Mar18_09-23-06_4a1998b12619/events.out.tfevents.1710753825.4a1998b12619.129.0
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size
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size 13463
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