File size: 2,914 Bytes
dab4a1f |
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 71 72 73 74 75 |
---
library_name: transformers
license: other
base_model: nvidia/mit-b0
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: mit-b0_whitefly
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. -->
# mit-b0_whitefly
This model is a fine-tuned version of [nvidia/mit-b0](https://huggingface.co/nvidia/mit-b0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2644
- Mean Iou: 0.4948
- Mean Accuracy: 0.4968
- Overall Accuracy: 0.9893
- Accuracy Background: 0.9907
- Accuracy Whitefly: 0.0029
- Iou Background: 0.9893
- Iou Whitefly: 0.0004
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Background | Accuracy Whitefly | Iou Background | Iou Whitefly |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:-------------------:|:-----------------:|:--------------:|:------------:|
| 0.6275 | 0.4 | 20 | 0.6849 | 0.3529 | 0.4550 | 0.7049 | 0.7056 | 0.2044 | 0.7048 | 0.0010 |
| 0.4423 | 0.8 | 40 | 0.5826 | 0.4745 | 0.5157 | 0.9468 | 0.9480 | 0.0834 | 0.9468 | 0.0022 |
| 0.3793 | 1.2 | 60 | 0.4444 | 0.4868 | 0.4927 | 0.9731 | 0.9744 | 0.0110 | 0.9731 | 0.0006 |
| 0.3102 | 1.6 | 80 | 0.3347 | 0.4976 | 0.4986 | 0.9949 | 0.9963 | 0.0009 | 0.9949 | 0.0002 |
| 0.272 | 2.0 | 100 | 0.3100 | 0.4983 | 0.4991 | 0.9963 | 0.9977 | 0.0004 | 0.9963 | 0.0002 |
| 0.3003 | 2.4 | 120 | 0.2579 | 0.4983 | 0.4991 | 0.9965 | 0.9979 | 0.0003 | 0.9965 | 0.0001 |
| 0.2558 | 2.8 | 140 | 0.2644 | 0.4948 | 0.4968 | 0.9893 | 0.9907 | 0.0029 | 0.9893 | 0.0004 |
### Framework versions
- Transformers 4.44.1
- Pytorch 2.6.0+cpu
- Datasets 2.21.0
- Tokenizers 0.19.1
|