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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
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
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