2025-05-30_23-53-40
This model is a fine-tuned version of google/deeplabv3_mobilenet_v2_1.0_513 on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.5218
- Accuracy: 0.7286
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: 8
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.1046 | 1.0 | 2 | 0.7815 | 0.5 |
0.0928 | 2.0 | 4 | 0.6803 | 0.5143 |
0.1231 | 3.0 | 6 | 0.6336 | 0.6429 |
0.0788 | 4.0 | 8 | 0.5967 | 0.6714 |
0.0828 | 5.0 | 10 | 0.6340 | 0.5857 |
0.0583 | 6.0 | 12 | 0.6024 | 0.6429 |
0.0842 | 7.0 | 14 | 0.6859 | 0.5143 |
0.0901 | 8.0 | 16 | 0.5748 | 0.6714 |
0.0924 | 9.0 | 18 | 0.5445 | 0.7429 |
0.0851 | 10.0 | 20 | 0.5218 | 0.7286 |
Framework versions
- Transformers 4.52.3
- Pytorch 2.7.0+cu126
- Datasets 3.6.0
- Tokenizers 0.21.1
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google/deeplabv3_mobilenet_v2_1.0_513