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README.md
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glpn-kitti-finetuned-diode
This model is a fine-tuned version of vinvino02/glpn-kitti on the diode-subset dataset. It achieves the following results on the evaluation set:
- Loss: 0.8818
- Rmse: 0.7721
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- 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 | Rmse |
|---|---|---|---|---|
| No log | 1.0 | 10 | 0.8395 | nan |
| 0.9442 | 2.0 | 20 | 0.8097 | nan |
| 0.894 | 3.0 | 30 | 0.7852 | nan |
| 0.894 | 4.0 | 40 | 0.7784 | nan |
| 0.8759 | 5.0 | 50 | 0.7690 | nan |
| 0.8475 | 6.0 | 60 | 0.7591 | nan |
| 0.8475 | 7.0 | 70 | 0.7493 | nan |
| 0.8312 | 8.0 | 80 | 0.7440 | nan |
| 0.83 | 9.0 | 90 | 0.7400 | nan |
| 0.83 | 10.0 | 100 | 0.7404 | nan |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.2