---
license: bsd-3-clause
base_model: Salesforce/codet5-large
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: codet5-large-finetuned-py2cpp
  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-large-finetuned-py2cpp

This model is a fine-tuned version of [Salesforce/codet5-large](https://huggingface.co/Salesforce/codet5-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5811
- Bleu: 1.7782
- Gen Len: 19.0

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- 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 | Bleu   | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|
| No log        | 0.98  | 41   | 1.4340          | 1.1636 | 18.6571 |
| No log        | 1.99  | 83   | 0.8793          | 1.6009 | 19.0    |
| No log        | 2.99  | 125  | 0.7255          | 1.6991 | 19.0    |
| No log        | 4.0   | 167  | 0.6623          | 1.7248 | 19.0    |
| No log        | 4.98  | 208  | 0.6263          | 1.6321 | 19.0    |
| No log        | 5.99  | 250  | 0.6073          | 1.6506 | 19.0    |
| No log        | 6.99  | 292  | 0.5934          | 1.7734 | 19.0    |
| No log        | 8.0   | 334  | 0.5852          | 1.7891 | 19.0    |
| No log        | 8.98  | 375  | 0.5824          | 1.7787 | 19.0    |
| No log        | 9.82  | 410  | 0.5811          | 1.7782 | 19.0    |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.13.3