---
library_name: peft
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
datasets:
- financial_phrasebank
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. -->

# 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 financial_phrasebank dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2612
- Accuracy: {'accuracy': 0.8287247214197276}

## 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: Use OptimizerNames.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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                         |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------:|
| 0.6087        | 1.0   | 606  | 0.6192          | {'accuracy': 0.8018984729673958} |
| 0.4539        | 2.0   | 1212 | 0.5939          | {'accuracy': 0.8312009905076352} |
| 0.3768        | 3.0   | 1818 | 0.7302          | {'accuracy': 0.8283120099050764} |
| 0.3249        | 4.0   | 2424 | 0.7608          | {'accuracy': 0.8287247214197276} |
| 0.1923        | 5.0   | 3030 | 0.8825          | {'accuracy': 0.8283120099050764} |
| 0.1518        | 6.0   | 3636 | 1.0603          | {'accuracy': 0.8332645480808915} |
| 0.1068        | 7.0   | 4242 | 1.1702          | {'accuracy': 0.8262484523318201} |
| 0.0673        | 8.0   | 4848 | 1.2515          | {'accuracy': 0.8217086256706562} |
| 0.072         | 9.0   | 5454 | 1.2673          | {'accuracy': 0.8303755674783326} |
| 0.0315        | 10.0  | 6060 | 1.2612          | {'accuracy': 0.8287247214197276} |


### Framework versions

- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.6.0+cpu
- Datasets 3.5.0
- Tokenizers 0.21.1