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: []
---

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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: 0.8488
- Accuracy: {'accuracy': 0.8924438393464942}

## 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                         |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------------------:|
| 0.4284        | 1.0   | 1469  | 0.6122          | {'accuracy': 0.8515997277059224} |
| 0.318         | 2.0   | 2938  | 0.4710          | {'accuracy': 0.8686181075561606} |
| 0.3091        | 3.0   | 4407  | 0.3991          | {'accuracy': 0.8910823689584751} |
| 0.267         | 4.0   | 5876  | 0.3609          | {'accuracy': 0.9081007488087134} |
| 0.2111        | 5.0   | 7345  | 0.5392          | {'accuracy': 0.8876786929884275} |
| 0.2231        | 6.0   | 8814  | 0.6888          | {'accuracy': 0.8978897208985704} |
| 0.1116        | 7.0   | 10283 | 0.6468          | {'accuracy': 0.8965282505105514} |
| 0.1111        | 8.0   | 11752 | 0.8718          | {'accuracy': 0.8849557522123894} |
| 0.076         | 9.0   | 13221 | 0.8075          | {'accuracy': 0.8965282505105514} |
| 0.0672        | 10.0  | 14690 | 0.8488          | {'accuracy': 0.8924438393464942} |


### Framework versions

- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
