File size: 2,005 Bytes
4885087 72741f1 49b7480 6472c7f 49b7480 6472c7f 4885087 6472c7f 4885087 49b7480 6472c7f 4885087 6472c7f 49b7480 4885087 6472c7f 4885087 6472c7f 4885087 6472c7f 4885087 6472c7f 4885087 6472c7f 4885087 6472c7f 4885087 6472c7f 4885087 6472c7f 4885087 6472c7f 4885087 6472c7f 4885087 6472c7f 49b7480 4885087 6472c7f 4885087 6472c7f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 |
---
license: other
base_model: nvidia/segformer-b1-finetuned-ade-512-512
tags:
- vision
- image-segmentation
- generated_from_trainer
metrics:
- precision
- recall
model-index:
- name: segformer-b1-finetuned-segments-pv_v1_normalized_p100_4batch_try_7_31
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/mouadn773/huggingface/runs/tgjpuivw)
# segformer-b1-finetuned-segments-pv_v1_normalized_p100_4batch_try_7_31
This model is a fine-tuned version of [nvidia/segformer-b1-finetuned-ade-512-512](https://huggingface.co/nvidia/segformer-b1-finetuned-ade-512-512) on the mouadenna/satellite_PV_dataset_train_test_v1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0133
- Mean Iou: 0.8164
- Precision: 0.8785
- Recall: 0.9203
## 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: 0.0004
- train_batch_size: 4
- eval_batch_size: 4
- 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|
| 0.0151 | 0.9989 | 229 | 0.0133 | 0.8164 | 0.8785 | 0.9203 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1
|