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---
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
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