---
library_name: transformers
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: resnet50
  results:
  - task:
      name: Image Classification
      type: image-classification
    dataset:
      name: imagefolder
      type: imagefolder
      config: default
      split: validation
      args: default
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.9926
---

<!-- 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. -->

# resnet50

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0210
- Accuracy: 0.9926
- F1 Weighted: 0.9926
- F1 Macro: 0.9925
- Precision Weighted: 0.9926

## 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: 0.0003
- train_batch_size: 128
- eval_batch_size: 256
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 256
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted | F1 Macro | Precision Weighted |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:------------------:|
| 3.7125        | 1.0   | 193  | 0.1263          | 0.961    | 0.9604      | 0.9602   | 0.9628             |
| 0.1261        | 2.0   | 386  | 0.0376          | 0.9882   | 0.9882      | 0.9881   | 0.9885             |
| 0.0347        | 3.0   | 579  | 0.0232          | 0.9926   | 0.9926      | 0.9925   | 0.9927             |
| 0.0165        | 4.0   | 772  | 0.0238          | 0.992    | 0.992       | 0.9919   | 0.9921             |
| 0.0109        | 5.0   | 965  | 0.0210          | 0.9926   | 0.9926      | 0.9925   | 0.9926             |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2