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

# my_new_model

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: 0.4151
- Accuracy: 0.882
- F1: 0.8815
- Precision: 0.8825
- Recall: 0.882

## 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: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log        | 1.0   | 125  | 0.5276          | 0.846    | 0.8496 | 0.8591    | 0.846  |
| No log        | 2.0   | 250  | 0.3993          | 0.874    | 0.8755 | 0.8801    | 0.874  |
| No log        | 3.0   | 375  | 0.3623          | 0.878    | 0.8808 | 0.8896    | 0.878  |
| 0.5033        | 4.0   | 500  | 0.3386          | 0.898    | 0.8985 | 0.9005    | 0.898  |
| 0.5033        | 5.0   | 625  | 0.3791          | 0.884    | 0.8840 | 0.8850    | 0.884  |
| 0.5033        | 6.0   | 750  | 0.3490          | 0.898    | 0.8993 | 0.9020    | 0.898  |
| 0.5033        | 7.0   | 875  | 0.3899          | 0.89     | 0.8898 | 0.8897    | 0.89   |
| 0.1244        | 8.0   | 1000 | 0.4148          | 0.87     | 0.8690 | 0.8686    | 0.87   |
| 0.1244        | 9.0   | 1125 | 0.4030          | 0.888    | 0.8880 | 0.8887    | 0.888  |
| 0.1244        | 10.0  | 1250 | 0.4151          | 0.882    | 0.8815 | 0.8825    | 0.882  |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3