---
base_model: distilbert-base-uncased
library_name: peft
license: apache-2.0
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: distilbert-base-uncased-lora-text-classification
  results: []
---

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[<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/lizhanyang718/huggingface/runs/d9kvxf5d)
# 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: 0.8192
- Accuracy: {'accuracy': 0.878}

## 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  | 0.3417          | {'accuracy': 0.867} |
| No log        | 2.0   | 250  | 0.2960          | {'accuracy': 0.878} |
| No log        | 3.0   | 375  | 0.4010          | {'accuracy': 0.875} |
| 0.2767        | 4.0   | 500  | 0.5766          | {'accuracy': 0.874} |
| 0.2767        | 5.0   | 625  | 0.6314          | {'accuracy': 0.878} |
| 0.2767        | 6.0   | 750  | 0.6541          | {'accuracy': 0.883} |
| 0.2767        | 7.0   | 875  | 0.7353          | {'accuracy': 0.887} |
| 0.0442        | 8.0   | 1000 | 0.7776          | {'accuracy': 0.883} |
| 0.0442        | 9.0   | 1125 | 0.8157          | {'accuracy': 0.874} |
| 0.0442        | 10.0  | 1250 | 0.8192          | {'accuracy': 0.878} |


### Framework versions

- PEFT 0.11.1
- Transformers 4.43.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1