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---
library_name: transformers
license: apache-2.0
base_model: facebook/convnextv2-tiny-1k-224
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: grateful-shape-212
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. -->
# grateful-shape-212
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: 1.3777
- Accuracy: 0.2708
- Precision: 0.4203
- Recall: 0.2708
- F1: 0.3127
- Roc Auc: 0.5428
## 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: 256
- eval_batch_size: 256
- seed: 42
- 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: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 1.4367 | 1.0 | 17 | 1.3810 | 0.0898 | 0.4478 | 0.0898 | 0.1092 | 0.5060 |
| 1.3894 | 2.0 | 34 | 1.3751 | 0.1823 | 0.4052 | 0.1823 | 0.2266 | 0.5250 |
| 1.3619 | 3.0 | 51 | 1.3766 | 0.2422 | 0.4100 | 0.2422 | 0.2876 | 0.5369 |
| 1.3523 | 4.0 | 68 | 1.3776 | 0.2708 | 0.4238 | 0.2708 | 0.3132 | 0.5422 |
| 1.3475 | 5.0 | 85 | 1.3777 | 0.2708 | 0.4203 | 0.2708 | 0.3127 | 0.5428 |
### Framework versions
- Transformers 4.52.3
- Pytorch 2.7.0+cpu
- Datasets 3.6.0
- Tokenizers 0.21.0
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