| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: Salesforce/codet5-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - rouge |
| model-index: |
| - name: CodeT5-KeyPhrases-Filtered-Valid-Phase1 |
| results: [] |
| --- |
| |
| <!-- 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-KeyPhrases-Filtered-Valid-Phase1 |
|
|
| This model is a fine-tuned version of [Salesforce/codet5-base](https://huggingface.co/Salesforce/codet5-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5395 |
| - Rouge1: 0.3357 |
| - Rouge2: 0.1004 |
| - Rougel: 0.3230 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 14 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 8 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | |
| |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:| |
| | 1.2932 | 1.0 | 8 | 0.8983 | 0.2450 | 0.0317 | 0.2338 | |
| | 0.7191 | 2.0 | 16 | 0.7307 | 0.3123 | 0.0742 | 0.3011 | |
| | 0.812 | 3.0 | 24 | 0.6878 | 0.3304 | 0.0994 | 0.3186 | |
| | 0.4139 | 4.0 | 32 | 0.6456 | 0.3431 | 0.1057 | 0.3313 | |
| | 0.482 | 5.0 | 40 | 0.6134 | 0.3445 | 0.0942 | 0.3327 | |
| | 0.3675 | 6.0 | 48 | 0.5809 | 0.3318 | 0.0924 | 0.3210 | |
| | 0.4833 | 7.0 | 56 | 0.5530 | 0.3408 | 0.0963 | 0.3282 | |
| | 0.3695 | 8.0 | 64 | 0.5395 | 0.3357 | 0.1004 | 0.3230 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.52.4 |
| - Pytorch 2.6.0+cu124 |
| - Datasets 3.6.0 |
| - Tokenizers 0.21.1 |
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|
