---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
datasets:
- imdb
metrics:
- accuracy
- f1
model-index:
- name: bert-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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# bert-base-uncased-lora-text-classification

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the imdb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2267
- Accuracy: {'accuracy': 0.92824}
- F1: 0.9288

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy              | F1     |
|:-------------:|:-----:|:----:|:---------------:|:---------------------:|:------:|
| 0.2608        | 1.0   | 1563 | 0.2187          | {'accuracy': 0.91768} | 0.9177 |
| 0.246         | 2.0   | 3126 | 0.2070          | {'accuracy': 0.92096} | 0.9205 |
| 0.2056        | 3.0   | 4689 | 0.2051          | {'accuracy': 0.92572} | 0.9259 |
| 0.1748        | 4.0   | 6252 | 0.2570          | {'accuracy': 0.92288} | 0.9249 |
| 0.1494        | 5.0   | 7815 | 0.2267          | {'accuracy': 0.92824} | 0.9288 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0