---
base_model: bigcode/starencoder
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: starencoder-vd-25-75
  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. -->

# starencoder-vd-25-75

This model is a fine-tuned version of [bigcode/starencoder](https://huggingface.co/bigcode/starencoder) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7599
- Accuracy: 0.7019
- Precision: 0.7660
- Recall: 0.5883
- F1: 0.6655
- Roc Auc: 0.7028

## 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: 9e-06
- train_batch_size: 45
- eval_batch_size: 45
- seed: 420
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:-------:|
| 0.6213        | 1.0   | 551  | 0.5820          | 0.6628   | 0.6816    | 0.6212 | 0.6500 | 0.6631  |
| 0.5585        | 2.0   | 1102 | 0.5802          | 0.6690   | 0.7861    | 0.4715 | 0.5895 | 0.6706  |
| 0.5109        | 3.0   | 1653 | 0.5687          | 0.6886   | 0.7681    | 0.5474 | 0.6393 | 0.6897  |
| 0.4645        | 4.0   | 2204 | 0.5875          | 0.6973   | 0.7742    | 0.5640 | 0.6526 | 0.6984  |
| 0.4161        | 5.0   | 2755 | 0.5819          | 0.7097   | 0.7425    | 0.6491 | 0.6926 | 0.7101  |
| 0.3756        | 6.0   | 3306 | 0.6319          | 0.7058   | 0.7451    | 0.6327 | 0.6843 | 0.7064  |
| 0.3451        | 7.0   | 3857 | 0.6542          | 0.7025   | 0.7358    | 0.6394 | 0.6842 | 0.7030  |
| 0.3144        | 8.0   | 4408 | 0.7204          | 0.7017   | 0.7607    | 0.5955 | 0.6680 | 0.7025  |
| 0.2978        | 9.0   | 4959 | 0.7168          | 0.7032   | 0.7524    | 0.6130 | 0.6756 | 0.7040  |
| 0.2757        | 10.0  | 5510 | 0.7599          | 0.7019   | 0.7660    | 0.5883 | 0.6655 | 0.7028  |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.1.0.dev20230605+cu121
- Datasets 2.14.0
- Tokenizers 0.13.3