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---
license: apache-2.0
base_model: facebook/convnextv2-base-22k-384
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- f1
model-index:
- name: convnextv2-base-22k-384
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: train
args: default
metrics:
- name: F1
type: f1
value: 0.9913113141099743
---
<!-- 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-base-22k-384
This model is a fine-tuned version of [facebook/convnextv2-base-22k-384](https://huggingface.co/facebook/convnextv2-base-22k-384) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0069
- F1: 0.9913
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 | F1 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.1521 | 1.0 | 202 | 0.0982 | 0.8278 |
| 0.0664 | 2.0 | 404 | 0.0626 | 0.9079 |
| 0.1053 | 3.0 | 606 | 0.0356 | 0.9537 |
| 0.0432 | 4.0 | 808 | 0.0302 | 0.9703 |
| 0.0552 | 5.0 | 1010 | 0.0114 | 0.9827 |
| 0.0352 | 6.0 | 1212 | 0.0131 | 0.9824 |
| 0.0221 | 7.0 | 1414 | 0.0063 | 0.9943 |
| 0.0018 | 8.0 | 1616 | 0.0169 | 0.9824 |
| 0.0283 | 9.0 | 1818 | 0.0028 | 0.9971 |
| 0.0429 | 10.0 | 2020 | 0.0069 | 0.9913 |
### Framework versions
- Transformers 4.37.2
- Pytorch 1.12.1+cu102
- Datasets 2.16.1
- Tokenizers 0.15.1
|