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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6215
- Accuracy: {'accuracy': 0.8248666666666666}

## 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                         |
|:-------------:|:-----:|:-----:|:---------------:|:--------------------------------:|
| 0.4666        | 1.0   | 7500  | 0.5550          | {'accuracy': 0.8414}             |
| 0.537         | 2.0   | 15000 | 0.5152          | {'accuracy': 0.8277666666666667} |
| 0.5576        | 3.0   | 22500 | 0.4929          | {'accuracy': 0.8178}             |
| 0.5947        | 4.0   | 30000 | 0.4912          | {'accuracy': 0.8104}             |
| 0.5841        | 5.0   | 37500 | 0.5970          | {'accuracy': 0.8050666666666667} |
| 0.6447        | 6.0   | 45000 | 0.6422          | {'accuracy': 0.8114333333333333} |
| 0.5955        | 7.0   | 52500 | 0.5771          | {'accuracy': 0.8209}             |
| 0.5419        | 8.0   | 60000 | 0.5765          | {'accuracy': 0.821}              |
| 0.5966        | 9.0   | 67500 | 0.6055          | {'accuracy': 0.8230666666666666} |
| 0.5417        | 10.0  | 75000 | 0.6215          | {'accuracy': 0.8248666666666666} |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.13.2
