---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: distilbert-base-uncased
model-index:
- name: distilbert-base-uncased-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. -->

# distilbert-base-uncased-lora-text-classification

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6098
- Accuracy: {'accuracy': 0.37777777777777777}

## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                          |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------:|
| No log        | 1.0   | 405  | 2.0008          | {'accuracy': 0.37037037037037035} |
| 2.0177        | 2.0   | 810  | 2.0349          | {'accuracy': 0.3802469135802469}  |
| 1.8336        | 3.0   | 1215 | 2.0526          | {'accuracy': 0.35802469135802467} |
| 1.7547        | 4.0   | 1620 | 2.1418          | {'accuracy': 0.33827160493827163} |
| 1.5832        | 5.0   | 2025 | 2.2398          | {'accuracy': 0.36790123456790125} |
| 1.5832        | 6.0   | 2430 | 2.2712          | {'accuracy': 0.34814814814814815} |
| 1.4297        | 7.0   | 2835 | 2.3660          | {'accuracy': 0.3530864197530864}  |
| 1.2579        | 8.0   | 3240 | 2.4898          | {'accuracy': 0.36790123456790125} |
| 1.1612        | 9.0   | 3645 | 2.5870          | {'accuracy': 0.35802469135802467} |
| 0.9591        | 10.0  | 4050 | 2.6098          | {'accuracy': 0.37777777777777777} |


### Framework versions

- PEFT 0.10.0
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2