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README.md
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---
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license: other
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base_model: google/mobilenet_v2_1.0_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: mobilenet_v2_1.0_224-finetuned-32bs-0.1lr
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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: 0.6468862515002001
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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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# mobilenet_v2_1.0_224-finetuned-32bs-0.1lr
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This model is a fine-tuned version of [google/mobilenet_v2_1.0_224](https://huggingface.co/google/mobilenet_v2_1.0_224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9270
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- Accuracy: 0.6469
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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: 0.1
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- train_batch_size: 32
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 512
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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: 3
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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 | 0.99 | 53 | 1.3949 | 0.4049 |
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| No log | 1.99 | 107 | 1.0455 | 0.5819 |
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| No log | 2.96 | 159 | 0.9270 | 0.6469 |
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### Framework versions
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- Transformers 4.33.1
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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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