---
base_model: microsoft/codebert-base
tags:
- Text Generation
- generated_from_trainer
model-index:
- name: codeBert-finetuned-cXg-nl-to-code
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# codeBert-finetuned-cXg-nl-to-code

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:
- eval_loss: 17.9546
- eval_rouge1: 0.0741
- eval_rouge2: 0.0047
- eval_rougeL: 0.0528
- eval_bleu: 1.0975
- eval_meteor: 0.0974
- eval_codebleu: {'codebleu': 0.2174788437391285, 'ngram_match_score': 0.0007172304133318851, 'weighted_ngram_match_score': 0.0015773932015006452, 'syntax_match_score': 0.07692307692307693, 'dataflow_match_score': 0.7906976744186046}
- eval_runtime: 40.1888
- eval_samples_per_second: 0.249
- eval_steps_per_second: 0.025
- step: 0

## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1