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: 0.0450
- Mean Iou: 0.9316
- Mean Accuracy: 0.9624
- Overall Accuracy: 0.9702
- Per Category Iou: [0.9489463592815923, 0.8807403310059301, 0.9650686948898038]
- Per Category Accuracy: [0.9718627711935148, 0.9278884306932264, 0.987556935702318]
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 |
|---|---|---|---|---|---|---|---|---|
| 0.0933 | 1.0 | 1405 | 0.0450 | 0.9316 | 0.9624 | 0.9702 | [0.9489463592815923, 0.8807403310059301, 0.9650686948898038] | [0.9718627711935148, 0.9278884306932264, 0.987556935702318] |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0