---
license: apache-2.0
base_model: Salesforce/codet5-small
tags:
- generated_from_trainer
datasets:
- code_x_glue_tc_text_to_code
metrics:
- rouge
model-index:
- name: codet5-small-java-v1-text-to-code
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: code_x_glue_tc_text_to_code
      type: code_x_glue_tc_text_to_code
      config: default
      split: validation
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 57.1969
---

<!-- 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-small-java-v1-text-to-code

This model is a fine-tuned version of [Salesforce/codet5-small](https://huggingface.co/Salesforce/codet5-small) on the code_x_glue_tc_text_to_code dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7705
- Rouge1: 57.1969
- Rouge2: 40.0098
- Rougel: 55.326
- Rougelsum: 56.119
- Gen Len: 16.8335

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.7434        | 1.0   | 6250  | 0.8148          | 55.9045 | 38.592  | 54.0278 | 54.7633   | 16.796  |
| 0.6708        | 2.0   | 12500 | 0.7868          | 56.3354 | 38.9843 | 54.5278 | 55.2197   | 16.751  |
| 0.6309        | 3.0   | 18750 | 0.7741          | 56.9883 | 39.8626 | 55.1321 | 55.9173   | 16.8495 |
| 0.6262        | 4.0   | 25000 | 0.7705          | 57.1969 | 40.0098 | 55.326  | 56.119    | 16.8335 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0