resnet-50
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: 1.0320
- Accuracy: 0.5186
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.3301 | 1.0 | 32 | 1.3377 | 0.3477 |
| 1.2001 | 2.0 | 64 | 1.2172 | 0.4414 |
| 1.1188 | 3.0 | 96 | 1.1265 | 0.5010 |
| 1.0655 | 4.0 | 128 | 1.1025 | 0.5010 |
| 1.0437 | 5.0 | 160 | 1.0753 | 0.5010 |
| 1.0374 | 6.0 | 192 | 1.0629 | 0.5029 |
| 1.0181 | 7.0 | 224 | 1.0452 | 0.5137 |
| 1.0011 | 8.0 | 256 | 1.0381 | 0.5127 |
| 1.0074 | 9.0 | 288 | 1.0268 | 0.5098 |
| 0.9977 | 10.0 | 320 | 1.0320 | 0.5186 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0
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Base model
microsoft/resnet-50