---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilbert-training-4
  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-training-4

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: 0.0316
- Accuracy: 0.9944
- Precision: 0.9955
- Recall: 0.9822
- F1: 0.9888

## 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: 8
- eval_batch_size: 8
- 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 | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.5   | 262  | 0.0957          | 0.9817   | 0.9562    | 0.9711 | 0.9636 |
| No log        | 1.0   | 524  | 0.0390          | 0.9939   | 0.9977    | 0.9778 | 0.9877 |
| 0.1008        | 1.5   | 786  | 0.0361          | 0.9944   | 0.9955    | 0.9822 | 0.9888 |
| 0.1008        | 2.0   | 1048 | 0.0385          | 0.9922   | 0.9866    | 0.9822 | 0.9844 |
| 0.0331        | 2.5   | 1310 | 0.0270          | 0.9956   | 0.9977    | 0.9844 | 0.9911 |
| 0.0331        | 2.99  | 1572 | 0.0358          | 0.9939   | 0.9955    | 0.98   | 0.9877 |
| 0.0151        | 3.49  | 1834 | 0.0292          | 0.9956   | 0.9955    | 0.9867 | 0.9911 |
| 0.0151        | 3.99  | 2096 | 0.0316          | 0.9944   | 0.9955    | 0.9822 | 0.9888 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.2.0.dev20230913+cu121
- Tokenizers 0.13.3