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

# starclass_bert

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1168
- Accuracy: 0.9683
- Precision: 0.9718
- Recall: 0.9683
- F1: 0.9683

## 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: 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.2759        | 1.0   | 16   | 0.7935          | 0.9048   | 0.9073    | 0.9048 | 0.9043 |
| 0.5557        | 2.0   | 32   | 0.3849          | 0.9048   | 0.9133    | 0.9048 | 0.9029 |
| 0.3352        | 3.0   | 48   | 0.1927          | 0.9365   | 0.9418    | 0.9365 | 0.9372 |
| 0.1037        | 4.0   | 64   | 0.1253          | 0.9683   | 0.9718    | 0.9683 | 0.9683 |
| 0.0465        | 5.0   | 80   | 0.1168          | 0.9683   | 0.9718    | 0.9683 | 0.9683 |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.15.2