---
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: 0.1058
- Precision: 1.0
- Recall: 0.875
- F1: 0.9333
- Accuracy: 0.9714

## 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: 5e-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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 6    | 0.0000          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 2.0   | 12   | 0.0006          | 1.0       | 1.0    | 1.0    | 1.0      |
| No log        | 3.0   | 18   | 0.0344          | 1.0       | 0.875  | 0.9333 | 0.9714   |
| No log        | 4.0   | 24   | 0.0257          | 1.0       | 0.875  | 0.9333 | 0.9714   |
| No log        | 5.0   | 30   | 0.0473          | 1.0       | 0.875  | 0.9333 | 0.9714   |
| No log        | 6.0   | 36   | 0.0485          | 1.0       | 0.875  | 0.9333 | 0.9714   |
| No log        | 7.0   | 42   | 0.0581          | 1.0       | 0.875  | 0.9333 | 0.9714   |
| No log        | 8.0   | 48   | 0.0840          | 1.0       | 0.875  | 0.9333 | 0.9714   |
| No log        | 9.0   | 54   | 0.0998          | 1.0       | 0.875  | 0.9333 | 0.9714   |
| No log        | 10.0  | 60   | 0.1058          | 1.0       | 0.875  | 0.9333 | 0.9714   |


### Framework versions

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