resnet-50-finetuned-resnet50_0831
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: 0.0862
- Accuracy: 0.9764
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.9066 | 1.0 | 223 | 0.8770 | 0.6659 |
0.5407 | 2.0 | 446 | 0.4251 | 0.7867 |
0.3614 | 3.0 | 669 | 0.2009 | 0.9390 |
0.3016 | 4.0 | 892 | 0.1362 | 0.9582 |
0.2358 | 5.0 | 1115 | 0.1139 | 0.9676 |
0.247 | 6.0 | 1338 | 0.1081 | 0.9698 |
0.2135 | 7.0 | 1561 | 0.1027 | 0.9720 |
0.2043 | 8.0 | 1784 | 0.1026 | 0.9695 |
0.2165 | 9.0 | 2007 | 0.0957 | 0.9733 |
0.1983 | 10.0 | 2230 | 0.0936 | 0.9736 |
0.2116 | 11.0 | 2453 | 0.0949 | 0.9736 |
0.2341 | 12.0 | 2676 | 0.0905 | 0.9755 |
0.2004 | 13.0 | 2899 | 0.0901 | 0.9739 |
0.1956 | 14.0 | 3122 | 0.0877 | 0.9755 |
0.1668 | 15.0 | 3345 | 0.0847 | 0.9764 |
0.1855 | 16.0 | 3568 | 0.0850 | 0.9755 |
0.18 | 17.0 | 3791 | 0.0897 | 0.9745 |
0.1772 | 18.0 | 4014 | 0.0852 | 0.9755 |
0.1881 | 19.0 | 4237 | 0.0845 | 0.9764 |
0.2145 | 20.0 | 4460 | 0.0862 | 0.9764 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.1
- Datasets 2.4.0
- Tokenizers 0.12.1
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