| | ---
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| | library_name: transformers
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| | license: apache-2.0
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| | base_model: google/mt5-base
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| | tags:
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| | - generated_from_trainer
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| | datasets:
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| | - wikisql
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| | model-index:
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| | - name: mt5_base_EN_sch_wiki
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| | results: []
|
| | ---
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| |
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| | <!-- 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. -->
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| |
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| | # mt5_base_EN_sch_wiki
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| |
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| | This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on the wikisql dataset.
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| | It achieves the following results on the evaluation set:
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| | - Loss: nan
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| | - Rouge2 Precision: 0.0165
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| | - Rouge2 Recall: 0.0087
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| | - Rouge2 Fmeasure: 0.0111
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| |
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| | ## Model description
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| |
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| | More information needed
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| |
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| | ## Intended uses & limitations
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| |
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| | More information needed
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| |
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| | ## Training and evaluation data
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| |
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| | More information needed
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| |
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| | ## Training procedure
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| |
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| | ### Training hyperparameters
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| |
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| | The following hyperparameters were used during training:
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| | - learning_rate: 5e-05
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| | - train_batch_size: 14
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| | - eval_batch_size: 16
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| | - seed: 42
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| | - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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| | - lr_scheduler_type: linear
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| | - num_epochs: 15
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| | - mixed_precision_training: Native AMP
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| |
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| | ### Training results
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| |
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| | | Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
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| | |:-------------:|:-----:|:-----:|:---------------:|:----------------:|:-------------:|:---------------:|
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| | | 0.0 | 1.0 | 4627 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 2.0 | 9254 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 3.0 | 13881 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 4.0 | 18508 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 5.0 | 23135 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 6.0 | 27762 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 7.0 | 32389 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 8.0 | 37016 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 9.0 | 41643 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 10.0 | 46270 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 11.0 | 50897 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 12.0 | 55524 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 13.0 | 60151 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 14.0 | 64778 | nan | 0.0165 | 0.0087 | 0.0111 |
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| | | 0.0 | 15.0 | 69405 | nan | 0.0165 | 0.0087 | 0.0111 |
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| |
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| | ### Framework versions
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| |
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| | - Transformers 4.46.2
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| | - Pytorch 2.2.2
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| | - Datasets 2.16.1
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| | - Tokenizers 0.20.3
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| |
|
