---
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: []
---

<!-- 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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5043
- Accuracy: {'accuracy': 0.9479166666666666}

## 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: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                         |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|
| No log        | 1.0   | 431  | 0.2331          | {'accuracy': 0.90625}            |
| 0.4451        | 2.0   | 862  | 0.3140          | {'accuracy': 0.90625}            |
| 0.2963        | 3.0   | 1293 | 0.3216          | {'accuracy': 0.9322916666666666} |
| 0.25          | 4.0   | 1724 | 0.2690          | {'accuracy': 0.9270833333333334} |
| 0.2261        | 5.0   | 2155 | 0.2707          | {'accuracy': 0.9479166666666666} |
| 0.1511        | 6.0   | 2586 | 0.2543          | {'accuracy': 0.9427083333333334} |
| 0.1401        | 7.0   | 3017 | 0.3120          | {'accuracy': 0.9375}             |
| 0.1401        | 8.0   | 3448 | 0.2845          | {'accuracy': 0.953125}           |
| 0.086         | 9.0   | 3879 | 0.4018          | {'accuracy': 0.921875}           |
| 0.0583        | 10.0  | 4310 | 0.4593          | {'accuracy': 0.9427083333333334} |
| 0.0475        | 11.0  | 4741 | 0.4401          | {'accuracy': 0.953125}           |
| 0.0515        | 12.0  | 5172 | 0.4631          | {'accuracy': 0.9479166666666666} |
| 0.0291        | 13.0  | 5603 | 0.4593          | {'accuracy': 0.9479166666666666} |
| 0.0319        | 14.0  | 6034 | 0.5292          | {'accuracy': 0.9479166666666666} |
| 0.0319        | 15.0  | 6465 | 0.5043          | {'accuracy': 0.9479166666666666} |


### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.1+cu124
- Datasets 3.0.0
- Tokenizers 0.19.1