glpn-nyu-finetuned-diode-230530-193901
This model is a fine-tuned version of vinvino02/glpn-nyu on the diode-subset dataset. It achieves the following results on the evaluation set:
- Loss: 1.5356
- Mae: 3.1497
- Rmse: 3.6237
- Abs Rel: 6.0096
- Log Mae: 0.6926
- Log Rmse: 0.8186
- Delta1: 0.3020
- Delta2: 0.3077
- Delta3: 0.3094
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: 24
- eval_batch_size: 48
- seed: 2022
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Mae | Rmse | Abs Rel | Log Mae | Log Rmse | Delta1 | Delta2 | Delta3 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 1 | 1.5604 | 3.2768 | 3.8048 | 6.3111 | 0.7037 | 0.8347 | 0.2996 | 0.3073 | 0.3091 |
| No log | 2.0 | 2 | 1.5559 | 3.2536 | 3.7731 | 6.2584 | 0.7017 | 0.8319 | 0.2998 | 0.3073 | 0.3092 |
| No log | 3.0 | 3 | 1.5513 | 3.2298 | 3.7401 | 6.2034 | 0.6997 | 0.8290 | 0.3002 | 0.3074 | 0.3092 |
| No log | 4.0 | 4 | 1.5469 | 3.2076 | 3.7083 | 6.1506 | 0.6977 | 0.8262 | 0.3006 | 0.3075 | 0.3093 |
| No log | 5.0 | 5 | 1.5434 | 3.1894 | 3.6815 | 6.1060 | 0.6961 | 0.8238 | 0.3011 | 0.3075 | 0.3093 |
| No log | 6.0 | 6 | 1.5407 | 3.1757 | 3.6614 | 6.0725 | 0.6949 | 0.8220 | 0.3015 | 0.3076 | 0.3094 |
| No log | 7.0 | 7 | 1.5387 | 3.1652 | 3.6460 | 6.0468 | 0.6940 | 0.8207 | 0.3017 | 0.3076 | 0.3094 |
| No log | 8.0 | 8 | 1.5371 | 3.1574 | 3.6348 | 6.0281 | 0.6933 | 0.8196 | 0.3019 | 0.3077 | 0.3094 |
| No log | 9.0 | 9 | 1.5361 | 3.1523 | 3.6273 | 6.0157 | 0.6928 | 0.8190 | 0.3020 | 0.3077 | 0.3094 |
| No log | 10.0 | 10 | 1.5356 | 3.1497 | 3.6237 | 6.0096 | 0.6926 | 0.8186 | 0.3020 | 0.3077 | 0.3094 |
Framework versions
- Transformers 4.29.2
- Pytorch 2.0.1+cu118
- Tokenizers 0.13.3
- Downloads last month
- 11
Model state unknown