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unet-efficientnet-b2-malaria-trophozoites-wbc

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unet-efficientnet-b2-malaria-trophozoites-wbc

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  1. README.md +143 -52
  2. model.safetensors +2 -2
  3. training_args.bin +1 -1
README.md CHANGED
@@ -1,55 +1,146 @@
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  ---
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- library_name: segmentation-models-pytorch
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- license: mit
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- pipeline_tag: image-segmentation
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  tags:
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- - model_hub_mixin
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- - pytorch_model_hub_mixin
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- - segmentation-models-pytorch
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- - semantic-segmentation
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- - pytorch
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- languages:
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- - python
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  ---
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- # Unet Model Card
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-
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- Table of Contents:
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- - [Load trained model](#load-trained-model)
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- - [Model init parameters](#model-init-parameters)
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- - [Model metrics](#model-metrics)
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- - [Dataset](#dataset)
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-
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- ## Load trained model
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- ```python
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- import segmentation_models_pytorch as smp
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-
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- model = smp.from_pretrained("<save-directory-or-this-repo>")
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- ```
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-
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- ## Model init parameters
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- ```python
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- model_init_params = {
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- "encoder_name": "efficientnet-b2",
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- "encoder_depth": 5,
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- "encoder_weights": "imagenet",
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- "decoder_use_batchnorm": True,
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- "decoder_channels": (256, 128, 64, 32, 16),
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- "decoder_attention_type": None,
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- "in_channels": 3,
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- "classes": 2,
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- "activation": None,
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- "aux_params": None
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- }
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- ```
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-
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- ## Model metrics
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- [More Information Needed]
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-
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- ## Dataset
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- Dataset name: [More Information Needed]
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-
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- ## More Information
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- - Library: https://github.com/qubvel/segmentation_models.pytorch
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- - Docs: https://smp.readthedocs.io/en/latest/
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-
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- This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ library_name: transformers
 
 
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  tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: unet-efficientnet-b2-malaria-trophozoites-wbc
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+ results: []
 
 
 
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  ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # unet-efficientnet-b2-malaria-trophozoites-wbc
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+
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+ This model was trained from scratch on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1470
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0003
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+ - train_batch_size: 16
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+ - eval_batch_size: 16
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_ratio: 0.02
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+ - num_epochs: 90
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | No log | 1.0 | 484 | 0.8717 |
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+ | 10.9992 | 2.0 | 968 | 0.1936 |
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+ | 0.2866 | 3.0 | 1452 | 0.1798 |
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+ | 0.1569 | 4.0 | 1936 | 0.1670 |
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+ | 0.1414 | 5.0 | 2420 | 0.1650 |
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+ | 0.1392 | 6.0 | 2904 | 0.1629 |
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+ | 0.1342 | 7.0 | 3388 | 0.1626 |
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+ | 0.1326 | 8.0 | 3872 | 0.1569 |
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+ | 0.1332 | 9.0 | 4356 | 0.1577 |
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+ | 0.1323 | 10.0 | 4840 | 0.1609 |
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+ | 0.1295 | 11.0 | 5324 | 0.1549 |
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+ | 0.127 | 12.0 | 5808 | 0.1552 |
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+ | 0.1277 | 13.0 | 6292 | 0.1560 |
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+ | 0.126 | 14.0 | 6776 | 0.1550 |
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+ | 0.1267 | 15.0 | 7260 | 0.1524 |
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+ | 0.1261 | 16.0 | 7744 | 0.1535 |
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+ | 0.131 | 17.0 | 8228 | 0.1541 |
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+ | 0.1258 | 18.0 | 8712 | 0.1532 |
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+ | 0.1232 | 19.0 | 9196 | 0.1505 |
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+ | 0.1258 | 20.0 | 9680 | 0.1616 |
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+ | 0.1257 | 21.0 | 10164 | 0.1547 |
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+ | 0.1251 | 22.0 | 10648 | 0.1516 |
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+ | 0.1264 | 23.0 | 11132 | 0.1512 |
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+ | 0.1221 | 24.0 | 11616 | 0.1527 |
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+ | 0.1239 | 25.0 | 12100 | 0.1536 |
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+ | 0.1221 | 26.0 | 12584 | 0.1520 |
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+ | 0.1272 | 27.0 | 13068 | 0.1515 |
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+ | 0.1214 | 28.0 | 13552 | 0.1522 |
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+ | 0.1211 | 29.0 | 14036 | 0.1490 |
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+ | 0.1202 | 30.0 | 14520 | 0.1515 |
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+ | 0.1256 | 31.0 | 15004 | 0.1503 |
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+ | 0.1256 | 32.0 | 15488 | 0.1513 |
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+ | 0.1215 | 33.0 | 15972 | 0.1494 |
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+ | 0.1222 | 34.0 | 16456 | 0.1516 |
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+ | 0.1226 | 35.0 | 16940 | 0.1507 |
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+ | 0.1218 | 36.0 | 17424 | 0.1493 |
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+ | 0.1222 | 37.0 | 17908 | 0.1529 |
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+ | 0.12 | 38.0 | 18392 | 0.1516 |
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+ | 0.1226 | 39.0 | 18876 | 0.1506 |
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+ | 0.1213 | 40.0 | 19360 | 0.1495 |
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+ | 0.1205 | 41.0 | 19844 | 0.1481 |
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+ | 0.1207 | 42.0 | 20328 | 0.1495 |
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+ | 0.1189 | 43.0 | 20812 | 0.1480 |
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+ | 0.1194 | 44.0 | 21296 | 0.1488 |
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+ | 0.1219 | 45.0 | 21780 | 0.1510 |
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+ | 0.1191 | 46.0 | 22264 | 0.1492 |
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+ | 0.1217 | 47.0 | 22748 | 0.1487 |
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+ | 0.1185 | 48.0 | 23232 | 0.1511 |
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+ | 0.1205 | 49.0 | 23716 | 0.1475 |
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+ | 0.1218 | 50.0 | 24200 | 0.1497 |
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+ | 0.1194 | 51.0 | 24684 | 0.1495 |
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+ | 0.1221 | 52.0 | 25168 | 0.1497 |
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+ | 0.1171 | 53.0 | 25652 | 0.1487 |
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+ | 0.1189 | 54.0 | 26136 | 0.1476 |
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+ | 0.1188 | 55.0 | 26620 | 0.1498 |
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+ | 0.1186 | 56.0 | 27104 | 0.1483 |
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+ | 0.1188 | 57.0 | 27588 | 0.1484 |
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+ | 0.1177 | 58.0 | 28072 | 0.1488 |
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+ | 0.1198 | 59.0 | 28556 | 0.1503 |
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+ | 0.1173 | 60.0 | 29040 | 0.1476 |
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+ | 0.1192 | 61.0 | 29524 | 0.1474 |
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+ | 0.1189 | 62.0 | 30008 | 0.1476 |
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+ | 0.1189 | 63.0 | 30492 | 0.1490 |
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+ | 0.1167 | 64.0 | 30976 | 0.1485 |
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+ | 0.1198 | 65.0 | 31460 | 0.1474 |
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+ | 0.1177 | 66.0 | 31944 | 0.1477 |
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+ | 0.1188 | 67.0 | 32428 | 0.1489 |
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+ | 0.1174 | 68.0 | 32912 | 0.1478 |
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+ | 0.1171 | 69.0 | 33396 | 0.1477 |
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+ | 0.12 | 70.0 | 33880 | 0.1483 |
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+ | 0.1188 | 71.0 | 34364 | 0.1475 |
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+ | 0.1172 | 72.0 | 34848 | 0.1477 |
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+ | 0.1174 | 73.0 | 35332 | 0.1474 |
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+ | 0.1174 | 74.0 | 35816 | 0.1487 |
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+ | 0.1174 | 75.0 | 36300 | 0.1484 |
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+ | 0.1178 | 76.0 | 36784 | 0.1478 |
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+ | 0.1169 | 77.0 | 37268 | 0.1488 |
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+ | 0.1182 | 78.0 | 37752 | 0.1478 |
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+ | 0.1132 | 79.0 | 38236 | 0.1477 |
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+ | 0.1175 | 80.0 | 38720 | 0.1472 |
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+ | 0.1142 | 81.0 | 39204 | 0.1473 |
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+ | 0.1176 | 82.0 | 39688 | 0.1475 |
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+ | 0.118 | 83.0 | 40172 | 0.1476 |
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+ | 0.1168 | 84.0 | 40656 | 0.1475 |
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+ | 0.116 | 85.0 | 41140 | 0.1475 |
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+ | 0.116 | 86.0 | 41624 | 0.1472 |
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+ | 0.1164 | 87.0 | 42108 | 0.1472 |
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+ | 0.1149 | 88.0 | 42592 | 0.1474 |
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+ | 0.1144 | 89.0 | 43076 | 0.1471 |
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+ | 0.1154 | 90.0 | 43560 | 0.1470 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.48.3
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.3.0
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+ - Tokenizers 0.21.0
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