---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/johanneseboigbe55-octave-analytics/huggingface/runs/ypukib7l)
# distilbert-base-uncased-lora-text-classification

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8006
- Accuracy: {'accuracy': 0.893}

## 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: 8
- eval_batch_size: 8
- 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   | 125  | 0.2598          | {'accuracy': 0.896} |
| No log        | 2.0   | 250  | 0.3580          | {'accuracy': 0.888} |
| No log        | 3.0   | 375  | 0.4035          | {'accuracy': 0.885} |
| 0.2622        | 4.0   | 500  | 0.5133          | {'accuracy': 0.881} |
| 0.2622        | 5.0   | 625  | 0.6146          | {'accuracy': 0.886} |
| 0.2622        | 6.0   | 750  | 0.7576          | {'accuracy': 0.885} |
| 0.2622        | 7.0   | 875  | 0.7499          | {'accuracy': 0.885} |
| 0.045         | 8.0   | 1000 | 0.8082          | {'accuracy': 0.891} |
| 0.045         | 9.0   | 1125 | 0.8045          | {'accuracy': 0.89}  |
| 0.045         | 10.0  | 1250 | 0.8006          | {'accuracy': 0.893} |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1