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---
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 |