peft tensorboard safetensors generated_from_trainer base_model:distilbert-base-uncased license:apache-2.0 region:us
---
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: []
library_name: peft
---

<!-- 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: 0.9528
- Accuracy: {'accuracy': 0.887}

## 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   | 250  | 0.3796          | {'accuracy': 0.88}  |
| 0.4157        | 2.0   | 500  | 0.4191          | {'accuracy': 0.879} |
| 0.4157        | 3.0   | 750  | 0.6114          | {'accuracy': 0.867} |
| 0.1906        | 4.0   | 1000 | 0.5635          | {'accuracy': 0.882} |
| 0.1906        | 5.0   | 1250 | 0.7240          | {'accuracy': 0.879} |
| 0.0727        | 6.0   | 1500 | 0.8097          | {'accuracy': 0.883} |
| 0.0727        | 7.0   | 1750 | 0.9097          | {'accuracy': 0.888} |
| 0.0275        | 8.0   | 2000 | 0.9154          | {'accuracy': 0.887} |
| 0.0275        | 9.0   | 2250 | 0.9432          | {'accuracy': 0.886} |
| 0.0133        | 10.0  | 2500 | 0.9528          | {'accuracy': 0.887} |


### Framework versions

- PEFT 0.4.0
- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
