---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: t5-small-generation-code-documentation
  results: []
widget:
- text: >-
    def get_training_corpus(threshold=256): dataset_corpus = dataset['train']
    for start_idx in range(0, len(dataset_corpus), 1000): samples =
    dataset_corpus[start_idx : start_idx + 1000] samples = [sample for sample in
    samples['func_code_tokens'] if len(sample) < threshold] yield samples
pipeline_tag: text2text-generation
---

<!-- 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. -->

# t5-small-generation-code-documentation

This model is a fine-tuned version of [t5-base](https://huggingface.co/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 6.0071

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- training_steps: 15000

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.4402        | 0.16  | 5000  | 6.2464          |
| 6.237         | 0.32  | 10000 | 6.0546          |
| 6.1603        | 0.48  | 15000 | 6.0071          |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.13.3