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

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# 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: 1.3644
- Accuracy: {'accuracy': 0.858}

## 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  | 0.3793          | {'accuracy': 0.856} |
| 0.435         | 2.0   | 500  | 0.5190          | {'accuracy': 0.858} |
| 0.435         | 3.0   | 750  | 0.8326          | {'accuracy': 0.857} |
| 0.2005        | 4.0   | 1000 | 0.9137          | {'accuracy': 0.856} |
| 0.2005        | 5.0   | 1250 | 1.0362          | {'accuracy': 0.862} |
| 0.0827        | 6.0   | 1500 | 1.2331          | {'accuracy': 0.852} |
| 0.0827        | 7.0   | 1750 | 1.2110          | {'accuracy': 0.856} |
| 0.033         | 8.0   | 2000 | 1.2963          | {'accuracy': 0.864} |
| 0.033         | 9.0   | 2250 | 1.3438          | {'accuracy': 0.863} |
| 0.0128        | 10.0  | 2500 | 1.3644          | {'accuracy': 0.858} |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.0
- Pytorch 2.1.1+cpu
- Datasets 2.15.0
- Tokenizers 0.15.0