---
library_name: transformers
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: deberta-v3-base-problematic-classifier-nd
  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-problematic-classifier-nd

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: 0.3997
- Accuracy: 0.92
- Auc: 0.971

## 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: 9e-05
- train_batch_size: 8
- eval_batch_size: 8
- 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: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
| 0.6785        | 1.0   | 132  | 0.6606          | 0.52     | 0.952 |
| 0.6426        | 2.0   | 264  | 0.6145          | 0.893    | 0.957 |
| 0.6033        | 3.0   | 396  | 0.5976          | 0.582    | 0.957 |
| 0.5587        | 4.0   | 528  | 0.5358          | 0.747    | 0.961 |
| 0.5397        | 5.0   | 660  | 0.4824          | 0.907    | 0.965 |
| 0.496         | 6.0   | 792  | 0.4506          | 0.911    | 0.968 |
| 0.456         | 7.0   | 924  | 0.4263          | 0.911    | 0.97  |
| 0.4502        | 8.0   | 1056 | 0.4118          | 0.916    | 0.97  |
| 0.438         | 9.0   | 1188 | 0.4060          | 0.911    | 0.971 |
| 0.4215        | 10.0  | 1320 | 0.3997          | 0.92     | 0.971 |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1