---
base_model: microsoft/codebert-base
tags:
- generated_from_trainer
model-index:
- name: CodeBertForCodeSummary
  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. -->

# CodeBertForCodeSummary

This model is a fine-tuned version of [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3533

## 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
- lr_scheduler_warmup_steps: 14400.0
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 5.051         | 1.0   | 750   | 4.6658          |
| 3.7963        | 2.0   | 1500  | 3.6102          |
| 3.2207        | 3.0   | 2250  | 2.9757          |
| 2.7558        | 4.0   | 3000  | 2.5950          |
| 2.4409        | 5.0   | 3750  | 2.3054          |
| 2.188         | 6.0   | 4500  | 2.0653          |
| 1.9616        | 7.0   | 5250  | 1.8439          |
| 1.7515        | 8.0   | 6000  | 1.6953          |
| 1.6408        | 9.0   | 6750  | 1.5872          |
| 1.4843        | 10.0  | 7500  | 1.5153          |
| 1.4453        | 11.0  | 8250  | 1.4662          |
| 1.3443        | 12.0  | 9000  | 1.4222          |
| 1.2826        | 13.0  | 9750  | 1.3990          |
| 1.2005        | 14.0  | 10500 | 1.3829          |
| 1.1559        | 15.0  | 11250 | 1.3678          |
| 1.0938        | 16.0  | 12000 | 1.3504          |
| 1.0285        | 17.0  | 12750 | 1.3493          |
| 0.9802        | 18.0  | 13500 | 1.3568          |
| 0.9333        | 19.0  | 14250 | 1.3549          |
| 0.8453        | 20.0  | 15000 | 1.3533          |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0