---
library_name: transformers
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: 2025-02-05-21-58-41-resnet-50
  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. -->

# 2025-02-05-21-58-41-resnet-50

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0762
- Precision: 0.9810
- Recall: 0.9805
- F1: 0.9804
- Accuracy: 0.9766
- Top1 Accuracy: 0.9805
- Error Rate: 0.0234

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- seed: 3407
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy | Top1 Accuracy | Error Rate |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------------:|:----------:|
| 2.4636        | 1.0   | 103  | 2.1548          | 0.6867    | 0.6293 | 0.5929 | 0.5824   | 0.6293        | 0.4176     |
| 1.3967        | 2.0   | 206  | 0.5586          | 0.8893    | 0.8780 | 0.8770 | 0.8743   | 0.8780        | 0.1257     |
| 0.4328        | 3.0   | 309  | 0.2100          | 0.9565    | 0.9512 | 0.9518 | 0.9524   | 0.9512        | 0.0476     |
| 0.2544        | 4.0   | 412  | 0.1414          | 0.9628    | 0.9610 | 0.9613 | 0.9588   | 0.9610        | 0.0412     |
| 0.171         | 5.0   | 515  | 0.1127          | 0.9690    | 0.9683 | 0.9683 | 0.9638   | 0.9683        | 0.0362     |
| 0.1556        | 6.0   | 618  | 0.0976          | 0.9715    | 0.9707 | 0.9706 | 0.9681   | 0.9707        | 0.0319     |
| 0.118         | 7.0   | 721  | 0.0762          | 0.9810    | 0.9805 | 0.9804 | 0.9766   | 0.9805        | 0.0234     |
| 0.1142        | 8.0   | 824  | 0.0853          | 0.9809    | 0.9805 | 0.9804 | 0.9813   | 0.9805        | 0.0187     |
| 0.0978        | 9.0   | 927  | 0.0798          | 0.9808    | 0.9805 | 0.9803 | 0.9788   | 0.9805        | 0.0212     |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.20.3