my_awesome_food_model_resnet
This model is a fine-tuned version of microsoft/resnet-50 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.4383
- Accuracy: 0.661
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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 4.2955 | 0.992 | 62 | 4.2486 | 0.18 |
| 3.4887 | 2.0 | 125 | 3.3899 | 0.312 |
| 2.7039 | 2.992 | 187 | 2.6616 | 0.475 |
| 2.1832 | 4.0 | 250 | 2.1833 | 0.565 |
| 1.946 | 4.992 | 312 | 1.9504 | 0.631 |
| 1.7753 | 6.0 | 375 | 1.7184 | 0.638 |
| 1.666 | 6.992 | 437 | 1.5985 | 0.667 |
| 1.5402 | 8.0 | 500 | 1.4900 | 0.667 |
| 1.5239 | 8.992 | 562 | 1.4500 | 0.665 |
| 1.5147 | 9.92 | 620 | 1.4383 | 0.661 |
Framework versions
- Transformers 4.45.0
- Pytorch 2.2.2+cu121
- Datasets 2.21.0
- Tokenizers 0.20.0
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Base model
microsoft/resnet-50