| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | model-index: |
| | - name: EN_mt5-base_5_wikiSQL_sch |
| | 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. --> |
| |
|
| | # EN_mt5-base_5_wikiSQL_sch |
| |
|
| | This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.0139 |
| | - Rouge2 Precision: 0.9436 |
| | - Rouge2 Recall: 0.8617 |
| | - Rouge2 Fmeasure: 0.8948 |
| |
|
| | ## 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: 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: 5 |
| |
|
| | ### Training results |
| |
|
| | | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure | |
| | |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:| |
| | | 0.0348 | 1.0 | 4049 | 0.0205 | 0.9264 | 0.85 | 0.8798 | |
| | | 0.0244 | 2.0 | 8098 | 0.0161 | 0.9377 | 0.8561 | 0.8891 | |
| | | 0.0185 | 3.0 | 12147 | 0.0146 | 0.9406 | 0.859 | 0.8919 | |
| | | 0.0167 | 4.0 | 16196 | 0.0143 | 0.9431 | 0.8613 | 0.8944 | |
| | | 0.0156 | 5.0 | 20245 | 0.0139 | 0.9436 | 0.8617 | 0.8948 | |
| |
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| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.26.1 |
| | - Pytorch 2.0.1+cu117 |
| | - Datasets 2.14.7.dev0 |
| | - Tokenizers 0.13.3 |
| |
|
