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: 1.3734
- Accuracy: {'accuracy': 0.6005221932114883}

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy                          |
|:-------------:|:-----:|:----:|:---------------:|:---------------------------------:|
| No log        | 1.0   | 192  | 1.8883          | {'accuracy': 0.36945169712793735} |
| No log        | 2.0   | 384  | 1.6563          | {'accuracy': 0.4216710182767624}  |
| 1.8736        | 3.0   | 576  | 1.5385          | {'accuracy': 0.46736292428198434} |
| 1.8736        | 4.0   | 768  | 1.4276          | {'accuracy': 0.5274151436031331}  |
| 1.8736        | 5.0   | 960  | 1.3666          | {'accuracy': 0.5613577023498695}  |
| 1.2939        | 6.0   | 1152 | 1.3688          | {'accuracy': 0.5613577023498695}  |
| 1.2939        | 7.0   | 1344 | 1.3397          | {'accuracy': 0.5783289817232375}  |
| 0.9487        | 8.0   | 1536 | 1.3576          | {'accuracy': 0.5757180156657964}  |
| 0.9487        | 9.0   | 1728 | 1.3523          | {'accuracy': 0.5939947780678851}  |
| 0.9487        | 10.0  | 1920 | 1.3819          | {'accuracy': 0.5926892950391645}  |
| 0.7324        | 11.0  | 2112 | 1.3746          | {'accuracy': 0.597911227154047}   |
| 0.7324        | 12.0  | 2304 | 1.3734          | {'accuracy': 0.6005221932114883}  |


### Framework versions

- Transformers 4.33.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3
