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---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: windowz_test-020525
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. -->
# windowz_test-020525
This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
It achieves the following results on the evaluation set:
- Model Preparation Time: 0.0011
- Accuracy: 0.9920
- F1: 0.9921
- Iou: 0.9850
- Contour Dice: 0.9925
- Loss: 0.0221
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100
### Training results
| Training Loss | Epoch | Step | Model Preparation Time | | Dice | Validation Loss |
|:-------------:|:-----:|:------:|:----------------------:|:------:|:------:|:---------------:|
| 0.4601 | 5.0 | 25630 | 0.0011 | 0.9713 | 0.9889 | 0.0642 |
| 0.4405 | 10.0 | 51260 | 0.0011 | 0.9760 | 0.9904 | 0.0372 |
| 0.3981 | 15.0 | 76890 | 0.0011 | 0.9793 | 0.9932 | 0.0316 |
| 0.361 | 20.0 | 102520 | 0.0011 | 0.9830 | 0.9925 | 0.0340 |
| 0.3978 | 25.0 | 128150 | 0.0011 | 0.9814 | 0.9903 | 0.0309 |
| 0.4293 | 30.0 | 153780 | 0.0011 | 0.9835 | 0.9923 | 0.0259 |
| 0.3522 | 35.0 | 179410 | 0.0011 | 0.9855 | 0.9927 | 0.0269 |
| 0.3718 | 40.0 | 205040 | 0.0011 | 0.9842 | 0.9931 | 0.0265 |
| 0.37 | 45.0 | 230670 | 0.0011 | 0.9851 | 0.9931 | 0.0242 |
| 0.3866 | 50.0 | 256300 | 0.0011 | 0.984 | 0.9920 | 0.0255 |
| 0.3416 | 55.0 | 281930 | 0.0011 | 0.9848 | 0.9930 | 0.0249 |
| 0.3461 | 60.0 | 307560 | 0.0011 | 0.9850 | 0.9925 | 0.0221 |
| 0.3509 | 65.0 | 333190 | 0.0011 | 0.9842 | 0.9919 | 0.0240 |
| 0.3616 | 70.0 | 358820 | 0.0011 | 0.9847 | 0.9931 | 0.0226 |
| 0.3406 | 75.0 | 384450 | 0.0011 | 0.9840 | 0.9926 | 0.0237 |
### Framework versions
- Transformers 4.45.0
- Pytorch 2.5.1+cu124
- Datasets 2.21.0
- Tokenizers 0.20.3
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