| | ---
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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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| | - f1
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| | model-index:
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| | - name: resnet_weather_model
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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: 0.6735537190082644
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| | - name: F1
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| | type: f1
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| | value: 0.6654635943888922
|
| | ---
|
| |
|
| | <!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| | should probably proofread and complete it, then remove this comment. -->
|
| |
|
| | # resnet_weather_model
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| |
|
| | This model was trained from scratch on the imagefolder dataset.
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| | It achieves the following results on the evaluation set:
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| | - Loss: 1.7452
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| | - Accuracy: 0.6736
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| | - F1: 0.6655
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| |
|
| | ## Model description
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| |
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| | More information needed
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| |
|
| | ## Intended uses & limitations
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| |
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| | More information needed
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| |
|
| | ## Training and evaluation data
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| |
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| | More information needed
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| |
|
| | ## Training procedure
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| |
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| | ### Training hyperparameters
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| |
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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: 8
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| | - eval_batch_size: 8
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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: 3
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| |
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| | ### Training results
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| |
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| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
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| | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
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| | | 2.3598 | 1.0 | 91 | 2.1983 | 0.5165 | 0.5146 |
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| | | 2.0319 | 2.0 | 182 | 1.8708 | 0.6446 | 0.6433 |
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| | | 1.7971 | 3.0 | 273 | 1.7452 | 0.6736 | 0.6655 |
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| |
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| |
|
| | ### Framework versions
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| |
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| | - Transformers 4.25.1
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| | - Pytorch 1.13.0+cu116
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| | - Datasets 2.8.0
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| | - Tokenizers 0.13.2
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| |
|
