---
library_name: transformers
license: apache-2.0
base_model: Salesforce/codet5-base
tags:
- generated_from_trainer
datasets:
- code_search_net
metrics:
- bleu
model-index:
- name: code_docstring_model
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: code_search_net
      type: code_search_net
      config: python
      split: validation
      args: python
    metrics:
    - name: Bleu
      type: bleu
      value: 0.01865929848556658
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# code_docstring_model

This model is a fine-tuned version of [Salesforce/codet5-base](https://huggingface.co/Salesforce/codet5-base) on the code_search_net dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9051
- Bleu: 0.0187

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Bleu   |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.111         | 1.0    | 1002 | 0.9781          | 0.0108 |
| 0.998         | 2.0    | 2004 | 0.9397          | 0.0109 |
| 0.9295        | 3.0    | 3006 | 0.9204          | 0.0120 |
| 0.8814        | 4.0    | 4008 | 0.9088          | 0.0159 |
| 0.8557        | 5.0    | 5010 | 0.9064          | 0.0171 |
| 0.8364        | 6.0    | 6012 | 0.9055          | 0.0180 |
| 0.8184        | 6.9933 | 7007 | 0.9051          | 0.0187 |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0