---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: DistillBERT-Political-Finetune
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# DistillBERT-Political-Finetune

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: 0.3916
- Accuracy: 0.8380
- F1: 0.8287
- Precision: 0.8410
- Recall: 0.8195

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5547        | 1.0   | 3845  | 0.3916          | 0.8380   | 0.8287 | 0.8410    | 0.8195 |
| 0.5061        | 2.0   | 7690  | 0.4957          | 0.8523   | 0.8409 | 0.8550    | 0.8309 |
| 0.1709        | 3.0   | 11535 | 0.5732          | 0.8575   | 0.8449 | 0.8541    | 0.8376 |
| 0.0965        | 4.0   | 15380 | 0.6933          | 0.8559   | 0.8438 | 0.8478    | 0.8406 |
| 0.063         | 5.0   | 19225 | 0.8462          | 0.8583   | 0.8444 | 0.8456    | 0.8433 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.19.1