unet-resnet18-malaria-trophozoites-wbc

README.md

@@ -1,55 +1,85 @@
 ---
-library_name: segmentation-models-pytorch
-license: mit
-pipeline_tag: image-segmentation
+library_name: transformers
 tags:
-- model_hub_mixin
-- pytorch_model_hub_mixin
-- segmentation-models-pytorch
-- semantic-segmentation
-- pytorch
-languages:
-- python
+- generated_from_trainer
+model-index:
+- name: unet-resnet18-malaria-trophozoites-wbc
+  results: []
 ---
-# Unet Model Card
-
-Table of Contents:
-- [Load trained model](#load-trained-model)
-- [Model init parameters](#model-init-parameters)
-- [Model metrics](#model-metrics)
-- [Dataset](#dataset)
-
-## Load trained model
-```python
-import segmentation_models_pytorch as smp
-
-model = smp.from_pretrained("<save-directory-or-this-repo>")
-```
-
-## Model init parameters
-```python
-model_init_params = {
-    "encoder_name": "resnet18",
-    "encoder_depth": 5,
-    "encoder_weights": "imagenet",
-    "decoder_use_batchnorm": True,
-    "decoder_channels": (256, 128, 64, 32, 16),
-    "decoder_attention_type": None,
-    "in_channels": 3,
-    "classes": 2,
-    "activation": None,
-    "aux_params": None
-}
-```
-
-## Model metrics
-[More Information Needed]
-
-## Dataset
-Dataset name: [More Information Needed]
-
-## More Information
-- Library: https://github.com/qubvel/segmentation_models.pytorch
-- Docs: https://smp.readthedocs.io/en/latest/
-
-This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin)
+
+<!-- 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. -->
+
+# unet-resnet18-malaria-trophozoites-wbc
+
+This model was trained from scratch on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0317
+
+## 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: 0.003
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 30
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| No log        | 1.0   | 211  | 0.1469          |
+| No log        | 2.0   | 422  | 0.0453          |
+| 0.1321        | 3.0   | 633  | 0.0406          |
+| 0.1321        | 4.0   | 844  | 0.0401          |
+| 0.0395        | 5.0   | 1055 | 0.0415          |
+| 0.0395        | 6.0   | 1266 | 0.0386          |
+| 0.0395        | 7.0   | 1477 | 0.0389          |
+| 0.0367        | 8.0   | 1688 | 0.0367          |
+| 0.0367        | 9.0   | 1899 | 0.0359          |
+| 0.0356        | 10.0  | 2110 | 0.0383          |
+| 0.0356        | 11.0  | 2321 | 0.0379          |
+| 0.0342        | 12.0  | 2532 | 0.0383          |
+| 0.0342        | 13.0  | 2743 | 0.0360          |
+| 0.0342        | 14.0  | 2954 | 0.0355          |
+| 0.0339        | 15.0  | 3165 | 0.0340          |
+| 0.0339        | 16.0  | 3376 | 0.0346          |
+| 0.0328        | 17.0  | 3587 | 0.0343          |
+| 0.0328        | 18.0  | 3798 | 0.0346          |
+| 0.0319        | 19.0  | 4009 | 0.0338          |
+| 0.0319        | 20.0  | 4220 | 0.0348          |
+| 0.0319        | 21.0  | 4431 | 0.0333          |
+| 0.0313        | 22.0  | 4642 | 0.0342          |
+| 0.0313        | 23.0  | 4853 | 0.0334          |
+| 0.0314        | 24.0  | 5064 | 0.0327          |
+| 0.0314        | 25.0  | 5275 | 0.0328          |
+| 0.0314        | 26.0  | 5486 | 0.0327          |
+| 0.0304        | 27.0  | 5697 | 0.0324          |
+| 0.0304        | 28.0  | 5908 | 0.0321          |
+| 0.0303        | 29.0  | 6119 | 0.0320          |
+| 0.0303        | 30.0  | 6330 | 0.0317          |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.3.0
+- Tokenizers 0.21.0

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