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

# finetuned_distilbert_model

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0728
- Precision: 0.6674
- Recall: 0.6483
- F1: 0.6577
- Accuracy: 0.9705

## 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: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0818        | 1.0   | 2185 | 0.0766          | 0.6435    | 0.5998 | 0.6209 | 0.9692   |
| 0.0709        | 2.0   | 4370 | 0.0739          | 0.6532    | 0.6241 | 0.6383 | 0.9700   |
| 0.0638        | 3.0   | 6555 | 0.0728          | 0.6674    | 0.6483 | 0.6577 | 0.9705   |
| 0.0579        | 4.0   | 8740 | 0.0753          | 0.6592    | 0.6813 | 0.6701 | 0.9698   |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1