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: 0.0486
- Mean Iou: 0.9290
- Mean Accuracy: 0.9613
- Overall Accuracy: 0.9689
- Per Category Iou: [0.9479483232482238, 0.8761366638834206, 0.9630055275754064]
- Per Category Accuracy: [0.9715740329423541, 0.9266074721530069, 0.985718906585144]
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 |
|---|---|---|---|---|---|---|---|---|
| 0.1074 | 1.0 | 1405 | 0.0486 | 0.9290 | 0.9613 | 0.9689 | [0.9479483232482238, 0.8761366638834206, 0.9630055275754064] | [0.9715740329423541, 0.9266074721530069, 0.985718906585144] |
Framework versions
- Transformers 4.45.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0