---
license: apache-2.0
base_model: distilbert/distilbert-base-cased
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: my_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. -->

# my_distilbert

This model is a fine-tuned version of [distilbert/distilbert-base-cased](https://huggingface.co/distilbert/distilbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1515
- Precision: 0.8038
- Recall: 0.8108
- F1: 0.8073
- Accuracy: 0.9574

## 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: 30
- eval_batch_size: 30
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 400  | 0.1692          | 0.7741    | 0.7904 | 0.7822 | 0.9516   |
| 0.2767        | 2.0   | 800  | 0.1524          | 0.7875    | 0.8010 | 0.7942 | 0.9547   |
| 0.1341        | 3.0   | 1200 | 0.1505          | 0.8068    | 0.8050 | 0.8059 | 0.9567   |
| 0.1072        | 4.0   | 1600 | 0.1498          | 0.7968    | 0.8121 | 0.8044 | 0.9568   |
| 0.0884        | 5.0   | 2000 | 0.1515          | 0.8038    | 0.8108 | 0.8073 | 0.9574   |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.13.3