---
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: 0.0618
- Precision: 0.8889
- Recall: 0.8889
- F1: 0.8889
- Accuracy: 0.9773

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 23   | 0.3117          | 1.0       | 0.6667 | 0.8    | 0.9091   |
| No log        | 2.0   | 46   | 0.1638          | 0.7778    | 0.7778 | 0.7778 | 0.9318   |
| No log        | 3.0   | 69   | 0.1322          | 0.875     | 0.7778 | 0.8235 | 0.9545   |
| No log        | 4.0   | 92   | 0.0582          | 0.8889    | 0.8889 | 0.8889 | 0.9773   |
| No log        | 5.0   | 115  | 0.1196          | 0.8889    | 0.8889 | 0.8889 | 0.9773   |
| No log        | 6.0   | 138  | 0.0607          | 0.8889    | 0.8889 | 0.8889 | 0.9773   |
| No log        | 7.0   | 161  | 0.0918          | 0.8889    | 0.8889 | 0.8889 | 0.9773   |
| No log        | 8.0   | 184  | 0.0512          | 0.8889    | 0.8889 | 0.8889 | 0.9773   |
| No log        | 9.0   | 207  | 0.0521          | 0.8889    | 0.8889 | 0.8889 | 0.9773   |
| No log        | 10.0  | 230  | 0.0618          | 0.8889    | 0.8889 | 0.8889 | 0.9773   |


### Framework versions

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