---
license: apache-2.0
base_model: bert-base-uncased
tags:
- generated_from_trainer
metrics:
- precision
- recall
model-index:
- name: conjunction-classification-finetuned
  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. -->

# conjunction-classification-finetuned

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3628
- Precision: 0.9722
- Recall: 0.9630
- F1-score: 0.9659

## 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: 1e-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
- lr_scheduler_warmup_steps: 500
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1-score |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:--------:|
| 1.0373        | 1.0   | 59   | 1.0341          | 0.1154    | 0.3333 | 0.1714   |
| 1.0096        | 2.0   | 118  | 0.8995          | 0.4697    | 0.5556 | 0.4602   |
| 0.8291        | 3.0   | 177  | 0.7374          | 0.4833    | 0.6667 | 0.5402   |
| 0.6212        | 4.0   | 236  | 0.5642          | 0.8246    | 0.6970 | 0.6032   |
| 0.3968        | 5.0   | 295  | 0.3628          | 0.9722    | 0.9630 | 0.9659   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0