---
library_name: transformers
tags:
- generated_from_trainer
model-index:
- name: unet-resnet34-malaria-trophozoites-wbc
  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. -->

# unet-resnet34-malaria-trophozoites-wbc

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1531

## 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: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| No log        | 1.0   | 242   | 0.2605          |
| No log        | 2.0   | 484   | 0.2295          |
| 0.6582        | 3.0   | 726   | 0.1956          |
| 0.6582        | 4.0   | 968   | 0.2041          |
| 0.1668        | 5.0   | 1210  | 0.1908          |
| 0.1668        | 6.0   | 1452  | 0.1820          |
| 0.1603        | 7.0   | 1694  | 0.1835          |
| 0.1603        | 8.0   | 1936  | 0.1800          |
| 0.1545        | 9.0   | 2178  | 0.1878          |
| 0.1545        | 10.0  | 2420  | 0.1753          |
| 0.151         | 11.0  | 2662  | 0.1952          |
| 0.151         | 12.0  | 2904  | 0.1860          |
| 0.1454        | 13.0  | 3146  | 0.1827          |
| 0.1454        | 14.0  | 3388  | 0.1729          |
| 0.1441        | 15.0  | 3630  | 0.1673          |
| 0.1441        | 16.0  | 3872  | 0.1707          |
| 0.1425        | 17.0  | 4114  | 0.1654          |
| 0.1425        | 18.0  | 4356  | 0.1667          |
| 0.1405        | 19.0  | 4598  | 0.1673          |
| 0.1405        | 20.0  | 4840  | 0.1699          |
| 0.1381        | 21.0  | 5082  | 0.1641          |
| 0.1381        | 22.0  | 5324  | 0.1654          |
| 0.141         | 23.0  | 5566  | 0.1670          |
| 0.141         | 24.0  | 5808  | 0.1658          |
| 0.136         | 25.0  | 6050  | 0.1678          |
| 0.136         | 26.0  | 6292  | 0.1623          |
| 0.136         | 27.0  | 6534  | 0.1640          |
| 0.136         | 28.0  | 6776  | 0.1618          |
| 0.1326        | 29.0  | 7018  | 0.1594          |
| 0.1326        | 30.0  | 7260  | 0.1611          |
| 0.1337        | 31.0  | 7502  | 0.1623          |
| 0.1337        | 32.0  | 7744  | 0.1599          |
| 0.1337        | 33.0  | 7986  | 0.1588          |
| 0.1301        | 34.0  | 8228  | 0.1583          |
| 0.1301        | 35.0  | 8470  | 0.1585          |
| 0.1301        | 36.0  | 8712  | 0.1569          |
| 0.1301        | 37.0  | 8954  | 0.1573          |
| 0.1298        | 38.0  | 9196  | 0.1562          |
| 0.1298        | 39.0  | 9438  | 0.1581          |
| 0.1309        | 40.0  | 9680  | 0.1568          |
| 0.1309        | 41.0  | 9922  | 0.1558          |
| 0.1274        | 42.0  | 10164 | 0.1552          |
| 0.1274        | 43.0  | 10406 | 0.1553          |
| 0.127         | 44.0  | 10648 | 0.1567          |
| 0.127         | 45.0  | 10890 | 0.1542          |
| 0.1278        | 46.0  | 11132 | 0.1545          |
| 0.1278        | 47.0  | 11374 | 0.1549          |
| 0.1275        | 48.0  | 11616 | 0.1535          |
| 0.1275        | 49.0  | 11858 | 0.1541          |
| 0.126         | 50.0  | 12100 | 0.1531          |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.0
- Tokenizers 0.21.0