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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
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