metadata
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: glacier_segmentation_transformer
results: []
glacier_segmentation_transformer
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0442
- Mean Iou: 0.9324
- Mean Accuracy: 0.9633
- Overall Accuracy: 0.9704
- Per Category Iou: [0.9492969014052214, 0.8833148832537979, 0.9646684118247586]
- Per Category Accuracy: [0.97225521704602, 0.9314524772776496, 0.9862309492005294]
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: 0.00018
- train_batch_size: 100
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou | Per Category Accuracy |
|---|---|---|---|---|---|---|---|---|
| 0.0545 | 1.0 | 2926 | 0.0442 | 0.9324 | 0.9633 | 0.9704 | [0.9492969014052214, 0.8833148832537979, 0.9646684118247586] | [0.97225521704602, 0.9314524772776496, 0.9862309492005294] |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0