---
tags:
- generated_from_trainer
model-index:
- name: codebert-python-custom-functions-dataset-python
  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. -->

# codebert-python-custom-functions-dataset-python

This model is a fine-tuned version of [neulab/codebert-python](https://huggingface.co/neulab/codebert-python) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0151

## 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: 2e-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
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.9043        | 1.0   | 43   | 1.5089          |
| 0.5831        | 2.0   | 86   | 0.4039          |
| 0.3148        | 3.0   | 129  | 0.1510          |
| 0.2251        | 4.0   | 172  | 0.0710          |
| 0.0766        | 5.0   | 215  | 0.0442          |
| 0.0884        | 6.0   | 258  | 0.0287          |
| 0.0975        | 7.0   | 301  | 0.0210          |
| 0.1113        | 8.0   | 344  | 0.0183          |
| 0.0448        | 9.0   | 387  | 0.0162          |
| 0.029         | 10.0  | 430  | 0.0151          |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3