|
--- |
|
license: apache-2.0 |
|
base_model: facebook/convnextv2-tiny-22k-384 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- imagefolder |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: convnext-tiny-new-1e-4-batch-32 |
|
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: 0.9404761904761905 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# convnext-tiny-new-1e-4-batch-32 |
|
|
|
This model is a fine-tuned version of [facebook/convnextv2-tiny-22k-384](https://huggingface.co/facebook/convnextv2-tiny-22k-384) on the imagefolder dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.2265 |
|
- Accuracy: 0.9405 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- num_epochs: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.7731 | 1.0 | 550 | 0.4237 | 0.8839 | |
|
| 0.6206 | 2.0 | 1100 | 0.3756 | 0.8930 | |
|
| 0.5014 | 3.0 | 1650 | 0.3272 | 0.9074 | |
|
| 0.3892 | 4.0 | 2200 | 0.2729 | 0.9280 | |
|
| 0.3819 | 5.0 | 2750 | 0.2953 | 0.9205 | |
|
| 0.3315 | 6.0 | 3300 | 0.2784 | 0.9260 | |
|
| 0.281 | 7.0 | 3850 | 0.2535 | 0.9328 | |
|
| 0.217 | 8.0 | 4400 | 0.2498 | 0.9344 | |
|
| 0.2152 | 9.0 | 4950 | 0.2405 | 0.9400 | |
|
| 0.2185 | 10.0 | 5500 | 0.2370 | 0.9400 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.39.3 |
|
- Pytorch 2.1.2 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|