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Model save
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README.md
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---
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license: apache-2.0
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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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- imagefolder
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metrics:
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- accuracy
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model-index:
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- name: image_classification_obipix_birdID
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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: 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: 0.9719696025912545
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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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# image_classification_obipix_birdID
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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: 0.1150
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- Accuracy: 0.9720
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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: 0.0002
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- train_batch_size: 64
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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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- 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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| 6.9257 | 0.18 | 1000 | 5.3830 | 0.1638 |
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| 3.9727 | 0.35 | 2000 | 2.7695 | 0.4797 |
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| 2.057 | 0.53 | 3000 | 1.5070 | 0.6936 |
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| 1.2103 | 0.7 | 4000 | 0.9727 | 0.7842 |
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| 0.8513 | 0.88 | 5000 | 0.7101 | 0.8318 |
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| 0.5836 | 1.06 | 6000 | 0.5797 | 0.8561 |
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| 0.3545 | 1.23 | 7000 | 0.5066 | 0.8730 |
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| 0.314 | 1.41 | 8000 | 0.4521 | 0.8818 |
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| 0.2858 | 1.58 | 9000 | 0.3915 | 0.8960 |
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| 0.2482 | 1.76 | 10000 | 0.3564 | 0.9056 |
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| 0.2192 | 1.93 | 11000 | 0.3131 | 0.9148 |
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| 0.1271 | 2.11 | 12000 | 0.2916 | 0.9207 |
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| 0.0779 | 2.29 | 13000 | 0.2727 | 0.9260 |
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| 0.0749 | 2.46 | 14000 | 0.2597 | 0.9309 |
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| 0.0682 | 2.64 | 15000 | 0.2415 | 0.9355 |
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| 0.0615 | 2.81 | 16000 | 0.2268 | 0.9385 |
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| 0.0566 | 2.99 | 17000 | 0.2084 | 0.9440 |
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| 0.0197 | 3.17 | 18000 | 0.1951 | 0.9475 |
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| 0.0158 | 3.34 | 19000 | 0.1843 | 0.9513 |
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| 0.0145 | 3.52 | 20000 | 0.1746 | 0.9541 |
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| 0.0118 | 3.69 | 21000 | 0.1649 | 0.9573 |
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| 0.0103 | 3.87 | 22000 | 0.1531 | 0.9599 |
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| 0.006 | 4.05 | 23000 | 0.1379 | 0.9644 |
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| 0.0016 | 4.22 | 24000 | 0.1316 | 0.9668 |
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| 0.0013 | 4.4 | 25000 | 0.1265 | 0.9686 |
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| 0.0014 | 4.57 | 26000 | 0.1232 | 0.9697 |
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| 0.0009 | 4.75 | 27000 | 0.1189 | 0.9712 |
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| 0.001 | 4.92 | 28000 | 0.1150 | 0.9720 |
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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 0.15.0
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runs/Mar18_12-43-54_user-desktop/events.out.tfevents.1710746066.user-desktop.44603.0
CHANGED
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version https://git-lfs.github.com/spec/v1
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size
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version https://git-lfs.github.com/spec/v1
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oid sha256:8d61fc19ff420bc3125ea689dd6a6f02197fe84287a5151cb737f118ae026f63
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size 218706
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