---
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnextv2-tiny-1k-224-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. -->

# convnextv2-tiny-1k-224-finetuned-galaxy10-decals

This model is a fine-tuned version of [facebook/convnextv2-tiny-1k-224](https://huggingface.co/facebook/convnextv2-tiny-1k-224) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4261
- Accuracy: 0.8703

## 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: 5e-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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.4287        | 0.9940  | 124  | 1.2978          | 0.5851   |
| 0.8329        | 1.9960  | 249  | 0.6987          | 0.7728   |
| 0.7348        | 2.9980  | 374  | 0.5659          | 0.8179   |
| 0.611         | 4.0     | 499  | 0.5379          | 0.8298   |
| 0.5929        | 4.9940  | 623  | 0.4972          | 0.8377   |
| 0.5227        | 5.9960  | 748  | 0.4715          | 0.8478   |
| 0.5166        | 6.9980  | 873  | 0.4761          | 0.8495   |
| 0.4992        | 8.0     | 998  | 0.4320          | 0.8563   |
| 0.4528        | 8.9940  | 1122 | 0.4410          | 0.8641   |
| 0.4566        | 9.9960  | 1247 | 0.4297          | 0.8641   |
| 0.4294        | 10.9980 | 1372 | 0.4282          | 0.8608   |
| 0.3771        | 12.0    | 1497 | 0.4546          | 0.8546   |
| 0.4224        | 12.9940 | 1621 | 0.4489          | 0.8625   |
| 0.4099        | 13.9960 | 1746 | 0.4411          | 0.8625   |
| 0.3759        | 14.9980 | 1871 | 0.4317          | 0.8653   |
| 0.3692        | 16.0    | 1996 | 0.4304          | 0.8630   |
| 0.364         | 16.9940 | 2120 | 0.4330          | 0.8664   |
| 0.3636        | 17.9960 | 2245 | 0.4250          | 0.8681   |
| 0.3396        | 18.9980 | 2370 | 0.4275          | 0.8675   |
| 0.3057        | 19.8798 | 2480 | 0.4261          | 0.8703   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.1.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1