resnet-50-finetuned-FBark
This model is a fine-tuned version of microsoft/resnet-50 on the imagefolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.1079
- Precision: 0.9699
- Recall: 0.9779
- F1: 0.9735
- Accuracy: 0.9720
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 35
Training results
Framework versions
- Transformers 4.39.3
- Pytorch 2.2.0+cpu
- Datasets 2.19.0
- Tokenizers 0.15.1
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Model tree for alyzbane/resnet-50-finetuned-FBark
Base model
microsoft/resnet-50Evaluation results
- Precision on imagefolderself-reported0.970
- Recall on imagefolderself-reported0.978
- F1 on imagefolderself-reported0.973
- Accuracy on imagefolderself-reported0.972