| --- |
| 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 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.36.0.dev0 |
| - Pytorch 2.1.0+cu118 |
| - Datasets 2.15.0 |
| - Tokenizers 0.15.0 |
|
|
