| | --- |
| | library_name: transformers |
| | license: apache-2.0 |
| | base_model: T5-base |
| | tags: |
| | - generated_from_trainer |
| | metrics: |
| | - bleu |
| | - rouge |
| | model-index: |
| | - name: T5-JSON-OM-IMP |
| | 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. --> |
| |
|
| | # T5-JSON-OM-IMP |
| |
|
| | This model is a fine-tuned version of [T5-base](https://huggingface.co/T5-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0946 |
| | - Micro Precision: 0.3295 |
| | - Micro Recall: 0.3853 |
| | - Micro F1: 0.3552 |
| | - Macro Precision: 0.3295 |
| | - Macro Recall: 0.3853 |
| | - Macro F1: 0.3552 |
| | - Bleu: 77.6645 |
| | - Rouge1: 0.7910 |
| | - Rouge2: 0.5470 |
| |
|
| | ## 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: 8 |
| | - eval_batch_size: 8 |
| | - 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: 4 |
| | - mixed_precision_training: Native AMP |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Micro Precision | Micro Recall | Micro F1 | Macro Precision | Macro Recall | Macro F1 | Bleu | Rouge1 | Rouge2 | |
| | |:-------------:|:-----:|:----:|:---------------:|:---------------:|:------------:|:--------:|:---------------:|:------------:|:--------:|:-------:|:------:|:------:| |
| | | 0.1167 | 1.0 | 468 | 0.0975 | 0.2817 | 0.4680 | 0.3517 | 0.2817 | 0.4680 | 0.3517 | 75.2453 | 0.7657 | 0.5238 | |
| | | 0.1103 | 2.0 | 936 | 0.0953 | 0.2956 | 0.4421 | 0.3543 | 0.2956 | 0.4421 | 0.3543 | 75.8760 | 0.7700 | 0.5180 | |
| | | 0.1022 | 3.0 | 1404 | 0.0941 | 0.2897 | 0.4452 | 0.3510 | 0.2897 | 0.4452 | 0.3510 | 75.7205 | 0.7651 | 0.5213 | |
| | | 0.1072 | 4.0 | 1872 | 0.0946 | 0.3295 | 0.3853 | 0.3552 | 0.3295 | 0.3853 | 0.3552 | 77.6645 | 0.7910 | 0.5470 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.51.1 |
| | - Pytorch 2.8.0.dev20250409+cu128 |
| | - Datasets 3.5.0 |
| | - Tokenizers 0.21.1 |
| |
|
