metadata

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

codeBert-finetuned-cXg-nl-to-code

This model is a fine-tuned version of 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