---
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
  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

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: 0.3965
- Accuracy: 0.878
- Auc: 0.949

## 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   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
| 0.6782        | 1.0   | 263  | 0.6769          | 0.509    | 0.914 |
| 0.6296        | 2.0   | 526  | 0.5905          | 0.822    | 0.904 |
| 0.587         | 3.0   | 789  | 0.5380          | 0.829    | 0.919 |
| 0.5433        | 4.0   | 1052 | 0.5017          | 0.82     | 0.932 |
| 0.4995        | 5.0   | 1315 | 0.4558          | 0.842    | 0.941 |
| 0.4887        | 6.0   | 1578 | 0.4269          | 0.887    | 0.942 |
| 0.4638        | 7.0   | 1841 | 0.4143          | 0.867    | 0.944 |
| 0.4436        | 8.0   | 2104 | 0.3969          | 0.898    | 0.948 |
| 0.4387        | 9.0   | 2367 | 0.4003          | 0.873    | 0.948 |
| 0.434         | 10.0  | 2630 | 0.3965          | 0.878    | 0.949 |


### Framework versions

- Transformers 4.50.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.4.1
- Tokenizers 0.21.1