---
library_name: transformers
license: mit
base_model: microsoft/deberta-large-mnli
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-classifier_batch32
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# roberta-classifier_batch32

This model is a fine-tuned version of [microsoft/deberta-large-mnli](https://huggingface.co/microsoft/deberta-large-mnli) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1474
- Accuracy: 0.941
- Auc: 0.988

## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Auc   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|
| 0.2918        | 1.0   | 161  | 0.2840          | 0.889    | 0.976 |
| 0.2151        | 2.0   | 322  | 0.1792          | 0.923    | 0.984 |
| 0.193         | 3.0   | 483  | 0.1571          | 0.938    | 0.986 |
| 0.1756        | 4.0   | 644  | 0.1434          | 0.943    | 0.988 |
| 0.1623        | 5.0   | 805  | 0.1474          | 0.941    | 0.988 |


### Framework versions

- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1