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---
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
|