---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: resnet-50-2024_09_13-batch-size32_epochs150_freeze
  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. -->

# resnet-50-2024_09_13-batch-size32_epochs150_freeze

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- F1 Micro: 0.0002
- F1 Macro: 0.0002
- Roc Auc: 0.4995
- Accuracy: 0.0003
- Learning Rate: 0.0001

## 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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 150
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Roc Auc | Accuracy | Rate   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-------:|:--------:|:------:|
| No log        | 1.0   | 273  | nan             | 0.0      | 0.0      | 0.4995  | 0.0      | 0.001  |
| 0.0           | 2.0   | 546  | nan             | 0.0003   | 0.0004   | 0.4993  | 0.0007   | 0.001  |
| 0.0           | 3.0   | 819  | nan             | 0.0008   | 0.0010   | 0.4994  | 0.0017   | 0.001  |
| 0.0           | 4.0   | 1092 | nan             | 0.0      | 0.0      | 0.4991  | 0.0      | 0.001  |
| 0.0           | 5.0   | 1365 | nan             | 0.0005   | 0.0006   | 0.4994  | 0.0010   | 0.001  |
| 0.0           | 6.0   | 1638 | nan             | 0.0002   | 0.0002   | 0.4993  | 0.0003   | 0.001  |
| 0.0           | 7.0   | 1911 | nan             | 0.0      | 0.0      | 0.4993  | 0.0      | 0.0001 |
| 0.0           | 8.0   | 2184 | nan             | 0.0002   | 0.0002   | 0.4993  | 0.0003   | 0.0001 |
| 0.0           | 9.0   | 2457 | nan             | 0.0      | 0.0      | 0.4994  | 0.0      | 0.0001 |
| 0.0           | 10.0  | 2730 | nan             | 0.0003   | 0.0004   | 0.4994  | 0.0007   | 0.0001 |
| 0.0           | 11.0  | 3003 | nan             | 0.0      | 0.0      | 0.4994  | 0.0      | 0.0001 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1