---
library_name: peft
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-base-lora-text-classification
  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. -->

# roberta-base-lora-text-classification

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2259
- Accuracy: {'accuracy': 0.9357798165137615}

## 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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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                         |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------------------:|
| 0.268         | 1.0   | 4210  | 0.2460          | {'accuracy': 0.908256880733945}  |
| 0.2589        | 2.0   | 8420  | 0.2230          | {'accuracy': 0.9243119266055045} |
| 0.2229        | 3.0   | 12630 | 0.2091          | {'accuracy': 0.926605504587156}  |
| 0.2068        | 4.0   | 16840 | 0.2403          | {'accuracy': 0.9277522935779816} |
| 0.1923        | 5.0   | 21050 | 0.2259          | {'accuracy': 0.9357798165137615} |


### Framework versions

- PEFT 0.14.0
- Transformers 4.49.0
- Pytorch 2.5.1+cu118
- Datasets 3.3.2
- Tokenizers 0.21.0