---
base_model: ''
tags:
- generated_from_trainer
model-index:
- name: glacformer
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# glacformer

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0333
- Mean Iou: 0.9528
- Mean Accuracy: 0.9772
- Overall Accuracy: 0.9885
- Per Category Iou: [0.9855230058020051, 0.8845759711828091, 0.9883964861024538]
- Per Category Accuracy: [0.9921669407092866, 0.9462930795421282, 0.9931901963885149]

## 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: 6e-05
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Per Category Iou                                             | Per Category Accuracy                                        |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------------------------------------------------:|:------------------------------------------------------------:|
| 0.045         | 1.0   | 523  | 0.0421          | 0.9477   | 0.9795        | 0.9869           | [0.9852157890390353, 0.8719898483736556, 0.9857700613925825] | [0.9904340924248899, 0.9587586082053337, 0.9893900149083925] |
| 0.0372        | 2.0   | 1046 | 0.0333          | 0.9528   | 0.9772        | 0.9885           | [0.9855230058020051, 0.8845759711828091, 0.9883964861024538] | [0.9921669407092866, 0.9462930795421282, 0.9931901963885149] |


### Framework versions

- Transformers 4.31.0
- Pytorch 1.14.0.dev20221130+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3