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

# 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: 0.5336
- Accuracy: 0.765
- Precision: {'precision': 0.7894736842105263}
- Recall: {'recall': 0.6593406593406593}
- F1: {'f1': 0.7185628742514969}
- Tp: 60
- Fp: 16
- Tn: 93
- Fn: 31

## 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: 96
- eval_batch_size: 24
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision                         | Recall                         | F1                         | Tp | Fp | Tn | Fn |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------------------------:|:------------------------------:|:--------------------------:|:--:|:--:|:--:|:--:|
| 0.6134        | 2.0   | 18   | 0.5336          | 0.765    | {'precision': 0.7894736842105263} | {'recall': 0.6593406593406593} | {'f1': 0.7185628742514969} | 60 | 16 | 93 | 31 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0