|
--- |
|
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: 0.4169 |
|
- Accuracy: 0.8673 |
|
|
|
## 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: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:| |
|
| 1.0664 | 0.9978 | 112 | 0.9818 | 0.6725 | |
|
| 0.8019 | 1.9955 | 224 | 0.6333 | 0.7990 | |
|
| 0.6524 | 2.9933 | 336 | 0.5248 | 0.8341 | |
|
| 0.6339 | 4.0 | 449 | 0.4731 | 0.8447 | |
|
| 0.5178 | 4.9978 | 561 | 0.4537 | 0.8503 | |
|
| 0.5907 | 5.9955 | 673 | 0.4556 | 0.8472 | |
|
| 0.5292 | 6.9933 | 785 | 0.4169 | 0.8673 | |
|
| 0.5017 | 8.0 | 898 | 0.4107 | 0.8597 | |
|
| 0.4605 | 8.9978 | 1010 | 0.4062 | 0.8635 | |
|
| 0.4765 | 9.9777 | 1120 | 0.3980 | 0.8647 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.40.0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.0 |
|
- Tokenizers 0.19.1 |
|
|
