---
license: apache-2.0
base_model: microsoft/resnet-50
tags:
- image-classification
- vision
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: resnet-50-finetuned-galaxy10-decals
  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-finetuned-galaxy10-decals

This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on the matthieulel/galaxy10_decals dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5789
- Accuracy: 0.4138
- Precision: 0.4493
- Recall: 0.4138
- F1: 0.3134

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 2.2417        | 0.9940 | 124  | 2.2265          | 0.2373   | 0.0697    | 0.2373 | 0.1077 |
| 2.1616        | 1.9960 | 249  | 2.1268          | 0.1950   | 0.1132    | 0.1950 | 0.0889 |
| 2.0459        | 2.9980 | 374  | 1.9901          | 0.2401   | 0.1029    | 0.2401 | 0.1290 |
| 1.9203        | 4.0    | 499  | 1.8571          | 0.3303   | 0.3116    | 0.3303 | 0.2052 |
| 1.8347        | 4.9940 | 623  | 1.7692          | 0.3613   | 0.2694    | 0.3613 | 0.2457 |
| 1.7628        | 5.9960 | 748  | 1.6926          | 0.3850   | 0.4172    | 0.3850 | 0.2758 |
| 1.723         | 6.9980 | 873  | 1.6342          | 0.3985   | 0.4428    | 0.3985 | 0.2922 |
| 1.71          | 8.0    | 998  | 1.6071          | 0.4104   | 0.4369    | 0.4104 | 0.3122 |
| 1.6948        | 8.9940 | 1122 | 1.5789          | 0.4138   | 0.4493    | 0.4138 | 0.3134 |
| 1.656         | 9.9399 | 1240 | 1.5805          | 0.4053   | 0.4176    | 0.4053 | 0.3034 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.1.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1