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---
library_name: transformers
license: apache-2.0
base_model: facebook/convnext-tiny-224
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: convnext-tiny-224-finetuned
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. -->
# convnext-tiny-224-finetuned
This model is a fine-tuned version of [facebook/convnext-tiny-224](https://huggingface.co/facebook/convnext-tiny-224) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9429
- Logloss: 0.9429
- Accuracy: {'accuracy': 0.6371511068334937}
## 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 | Logloss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:-------:|:--------------------------------:|
| 1.4538 | 0.9846 | 32 | 1.3816 | 1.3816 | {'accuracy': 0.4475457170356112} |
| 1.2257 | 2.0 | 65 | 1.1411 | 1.1411 | {'accuracy': 0.5668912415784408} |
| 1.0432 | 2.9846 | 97 | 1.0302 | 1.0302 | {'accuracy': 0.6034648700673725} |
| 1.0002 | 4.0 | 130 | 0.9979 | 0.9979 | {'accuracy': 0.615014436958614} |
| 0.9492 | 4.9846 | 162 | 0.9781 | 0.9781 | {'accuracy': 0.631376323387873} |
| 0.9302 | 6.0 | 195 | 0.9664 | 0.9664 | {'accuracy': 0.629451395572666} |
| 0.8805 | 6.9846 | 227 | 0.9515 | 0.9515 | {'accuracy': 0.6371511068334937} |
| 0.852 | 8.0 | 260 | 0.9504 | 0.9504 | {'accuracy': 0.6256015399422522} |
| 0.8352 | 8.9846 | 292 | 0.9468 | 0.9468 | {'accuracy': 0.6371511068334937} |
| 0.8245 | 9.8462 | 320 | 0.9429 | 0.9429 | {'accuracy': 0.6371511068334937} |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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