HF计算机视觉
sayakpaul/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: 0.5845
- Rmse: 0.6175
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 | 0.8001 | 0.8455 |
| 0.8187 | 2.0 | 20 | 0.7558 | 0.7907 |
| 0.8187 | 3.0 | 30 | 0.7391 | 0.7379 |
| 0.7618 | 4.0 | 40 | 0.6937 | 0.6895 |
| 0.7618 | 5.0 | 50 | 0.6954 | nan |
| 0.6917 | 6.0 | 60 | 0.6834 | nan |
| 0.6917 | 7.0 | 70 | 0.6719 | nan |
| 0.6625 | 8.0 | 80 | 0.6634 | nan |
| 0.6625 | 9.0 | 90 | 0.6592 | nan |
| 0.6553 | 10.0 | 100 | 0.6579 | nan |
Framework versions
- Transformers 4.24.0
- PyTorch 1.12.1+cu113
- Tokenizers 0.13.2
数据统计
数据评估
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