---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: Distilbert
  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. -->

# Distilbert

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: 0.6418
- Accuracy: 0.7992
- F1: 0.7411
- Precision: 0.7935
- Recall: 0.6952

## 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: 32
- 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     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6496        | 1.0   | 32   | 0.5694          | 0.6811   | 0.5888 | 0.6304    | 0.5524 |
| 0.4365        | 2.0   | 64   | 0.5541          | 0.7441   | 0.6409 | 0.7632    | 0.5524 |
| 0.2431        | 3.0   | 96   | 0.5720          | 0.7795   | 0.7282 | 0.7426    | 0.7143 |
| 0.1262        | 4.0   | 128  | 0.5727          | 0.7874   | 0.7429 | 0.7429    | 0.7429 |
| 0.0742        | 5.0   | 160  | 0.6418          | 0.7992   | 0.7411 | 0.7935    | 0.6952 |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 2.20.0
- Tokenizers 0.20.0