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---
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-large-224
tags:
- generated_from_trainer
datasets:
- imagefolder
metrics:
- accuracy
model-index:
- name: weeds24_convnext_balanced
results:
- task:
name: Image Classification
type: image-classification
dataset:
name: imagefolder
type: imagefolder
config: default
split: test
args: default
metrics:
- name: Accuracy
type: accuracy
value: 0.94
---
<!-- 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. -->
# weeds24_convnext_balanced
This model is a fine-tuned version of [facebook/convnext-large-224](https://huggingface.co/facebook/convnext-large-224) on the imagefolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1908
- Accuracy: 0.94
## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 9.0308 | 1.0 | 75 | 2.0854 | 0.5067 |
| 4.0591 | 2.0 | 150 | 0.9363 | 0.8433 |
| 1.9789 | 3.0 | 225 | 0.5118 | 0.8867 |
| 1.3397 | 4.0 | 300 | 0.3700 | 0.9067 |
| 0.9292 | 5.0 | 375 | 0.2859 | 0.92 |
| 0.7772 | 6.0 | 450 | 0.2314 | 0.9233 |
| 0.8323 | 7.0 | 525 | 0.2472 | 0.9233 |
| 0.7398 | 8.0 | 600 | 0.2647 | 0.9233 |
| 0.6066 | 9.0 | 675 | 0.2107 | 0.9433 |
| 0.546 | 10.0 | 750 | 0.1908 | 0.94 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.5.0+cu124
- Datasets 3.0.2
- Tokenizers 0.20.1
|