---
library_name: transformers
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: finetuning-bert-text-classification
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# finetuning-bert-text-classification

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2394
- Accuracy: 0.9073

## 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: 2e-05
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 0.2612        | 1.0   | 6250  | 0.2394          | 0.9073   |
| 0.1966        | 2.0   | 12500 | 0.2488          | 0.9184   |
| 0.1737        | 3.0   | 18750 | 0.2759          | 0.9192   |
| 0.1415        | 4.0   | 25000 | 0.3322          | 0.9165   |
| 0.0857        | 5.0   | 31250 | 0.3835          | 0.9199   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1