---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- recall
- precision
- f1
model-index:
- name: model1
  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. -->

# model1

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: 0.0018
- Recall: 0.9997
- Precision: 0.9997
- F1: 0.9997

## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Recall | Precision | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|:---------:|:------:|
| 0.0238        | 1.0   | 856  | 0.0024          | 0.9995 | 0.9995    | 0.9995 |
| 0.0013        | 2.0   | 1712 | 0.0018          | 0.9997 | 0.9997    | 0.9997 |
| 0.0006        | 3.0   | 2568 | 0.0019          | 0.9997 | 0.9997    | 0.9997 |


### Framework versions

- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2