---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilbert-training-3
  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-3

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: 0.0197
- Accuracy: 0.9956
- Precision: 1.0
- Recall: 0.9910
- F1: 0.9955

## 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   | 131  | 0.1115          | 0.97     | 0.9976    | 0.9413 | 0.9686 |
| No log        | 1.0   | 262  | 0.0659          | 0.9844   | 1.0       | 0.9684 | 0.9839 |
| 0.1414        | 1.49  | 393  | 0.0632          | 0.9878   | 1.0       | 0.9752 | 0.9874 |
| 0.1414        | 1.99  | 524  | 0.0795          | 0.9822   | 1.0       | 0.9639 | 0.9816 |
| 0.0512        | 2.49  | 655  | 0.0542          | 0.9878   | 1.0       | 0.9752 | 0.9874 |
| 0.0512        | 2.99  | 786  | 0.0199          | 0.9944   | 1.0       | 0.9887 | 0.9943 |
| 0.0246        | 3.49  | 917  | 0.0202          | 0.9944   | 1.0       | 0.9887 | 0.9943 |
| 0.0246        | 3.98  | 1048 | 0.0197          | 0.9956   | 1.0       | 0.9910 | 0.9955 |


### Framework versions

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