---
license: apache-2.0
base_model: Salesforce/codet5-base
tags:
- code-generation
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: codeT5-finetuned-cXg-nl-to-code
  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. -->

# codeT5-finetuned-cXg-nl-to-code

This model is a fine-tuned version of [Salesforce/codet5-base](https://huggingface.co/Salesforce/codet5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4852
- Rouge1: 0.2602
- Rouge2: 0.0661
- Rougel: 0.2363
- Bleu: 11.1005
- Meteor: 0.3527
- Codebleu: 0.1717

## 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: 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Bleu   | Meteor | Codebleu |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:------:|:------:|:--------:|
| No log        | 1.0   | 4    | 1.0580          | 0.0867 | 0.0075 | 0.0826 | 0.3778 | 0.0859 | 0.0271   |
| No log        | 2.0   | 8    | 0.7338          | 0.1628 | 0.0330 | 0.1493 | 1.7546 | 0.2224 | 0.0420   |
| No log        | 3.0   | 12   | 0.6427          | 0.2150 | 0.0546 | 0.1959 | 3.3997 | 0.2411 | 0.0680   |
| No log        | 4.0   | 16   | 0.5162          | 0.2598 | 0.0579 | 0.2303 | 5.3818 | 0.2805 | 0.1065   |
| No log        | 5.0   | 20   | 0.4852          | 0.2578 | 0.0559 | 0.2346 | 6.1221 | 0.2829 | 0.1208   |


### Framework versions

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