---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-base_LOGIC_Native
  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. -->

# deberta-v3-base_LOGIC_Native

This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.1367
- Macro Precision: 0.0105
- Macro F1: 0.0185

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro Precision | Macro F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------:|:--------:|
| No log        | 1.0   | 116  | nan             | 0.1367   | 0.0105          | 0.0185   |
| No log        | 2.0   | 232  | nan             | 0.1367   | 0.0105          | 0.0185   |
| No log        | 3.0   | 348  | nan             | 0.1367   | 0.0105          | 0.0185   |
| No log        | 4.0   | 464  | nan             | 0.1367   | 0.0105          | 0.0185   |
| 2.4862        | 5.0   | 580  | nan             | 0.1367   | 0.0105          | 0.0185   |
| 2.4862        | 6.0   | 696  | nan             | 0.1367   | 0.0105          | 0.0185   |
| 2.4862        | 7.0   | 812  | nan             | 0.1367   | 0.0105          | 0.0185   |
| 2.4862        | 8.0   | 928  | nan             | 0.1367   | 0.0105          | 0.0185   |
| 0.0           | 9.0   | 1044 | nan             | 0.1367   | 0.0105          | 0.0185   |
| 0.0           | 10.0  | 1160 | nan             | 0.1367   | 0.0105          | 0.0185   |
| 0.0           | 11.0  | 1276 | nan             | 0.1367   | 0.0105          | 0.0185   |
| 0.0           | 12.0  | 1392 | nan             | 0.1367   | 0.0105          | 0.0185   |


### Framework versions

- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2