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

# distilbert_finetune_own_data_model

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0053
- Precision: 1.0
- Recall: 1.0
- F1: 1.0
- Accuracy: 1.0

## 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: 30

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 3    | 0.8131          | 1.0       | 0.25   | 0.4    | 0.76     |
| No log        | 2.0   | 6    | 0.6099          | 1.0       | 0.25   | 0.4    | 0.76     |
| No log        | 3.0   | 9    | 0.4666          | 1.0       | 0.25   | 0.4    | 0.76     |
| No log        | 4.0   | 12   | 0.3527          | 1.0       | 0.625  | 0.7692 | 0.88     |
| No log        | 5.0   | 15   | 0.2583          | 1.0       | 0.875  | 0.9333 | 0.96     |
| No log        | 6.0   | 18   | 0.1838          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 7.0   | 21   | 0.1230          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 8.0   | 24   | 0.0776          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 9.0   | 27   | 0.0543          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 10.0  | 30   | 0.0427          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 11.0  | 33   | 0.0378          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 12.0  | 36   | 0.0345          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 13.0  | 39   | 0.0323          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 14.0  | 42   | 0.0280          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 15.0  | 45   | 0.0228          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 16.0  | 48   | 0.0180          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 17.0  | 51   | 0.0141          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 18.0  | 54   | 0.0117          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 19.0  | 57   | 0.0104          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 20.0  | 60   | 0.0094          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 21.0  | 63   | 0.0086          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 22.0  | 66   | 0.0079          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 23.0  | 69   | 0.0074          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 24.0  | 72   | 0.0069          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 25.0  | 75   | 0.0063          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 26.0  | 78   | 0.0059          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 27.0  | 81   | 0.0056          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 28.0  | 84   | 0.0054          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 29.0  | 87   | 0.0053          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 30.0  | 90   | 0.0053          | 1.0       | 1.0    | 1.0    | 1.0      |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2