| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: ALL_mt5-base_10_wikiSQL |
| | 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. --> |
| |
|
| | # ALL_mt5-base_10_wikiSQL |
| | |
| | This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the None dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2056 |
| | - Rouge2 Precision: 0.7601 |
| | - Rouge2 Recall: 0.6878 |
| | - Rouge2 Fmeasure: 0.7165 |
| | |
| | ## 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: 5e-05 |
| | - train_batch_size: 35 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: linear |
| | - num_epochs: 10 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
| | |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
| | | 0.3197 | 1.0 | 3702 | 0.2658 | 0.7084 | 0.6348 | 0.6636 | |
| | | 0.2666 | 2.0 | 7404 | 0.2348 | 0.7294 | 0.6574 | 0.686 | |
| | | 0.2356 | 3.0 | 11106 | 0.2229 | 0.7409 | 0.6678 | 0.6968 | |
| | | 0.2169 | 4.0 | 14808 | 0.2162 | 0.7471 | 0.6747 | 0.7035 | |
| | | 0.2021 | 5.0 | 18510 | 0.2121 | 0.7513 | 0.6796 | 0.708 | |
| | | 0.1959 | 6.0 | 22212 | 0.2089 | 0.7545 | 0.6824 | 0.711 | |
| | | 0.1878 | 7.0 | 25914 | 0.2069 | 0.757 | 0.6848 | 0.7134 | |
| | | 0.1801 | 8.0 | 29616 | 0.2060 | 0.7586 | 0.6862 | 0.715 | |
| | | 0.1763 | 9.0 | 33318 | 0.2055 | 0.7594 | 0.6877 | 0.7161 | |
| | | 0.1752 | 10.0 | 37020 | 0.2056 | 0.7601 | 0.6878 | 0.7165 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.26.1 |
| | - Pytorch 2.1.2 |
| | - Datasets 2.16.1 |
| | - Tokenizers 0.13.3 |
| | |
