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metadata
library_name: transformers
license: apache-2.0
base_model: google/mt5-base
tags:
  - generated_from_trainer
datasets:
  - wikisql
model-index:
  - name: mt5_base_EN_sch_wiki
    results: []

mt5_base_EN_sch_wiki

This model is a fine-tuned version of google/mt5-base on the wikisql dataset. It achieves the following results on the evaluation set:

  • Loss: nan
  • Rouge2 Precision: 0.0165
  • Rouge2 Recall: 0.0087
  • Rouge2 Fmeasure: 0.0111

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: 14
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Use 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: 15
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge2 Precision Rouge2 Recall Rouge2 Fmeasure
0.0 1.0 4627 nan 0.0165 0.0087 0.0111
0.0 2.0 9254 nan 0.0165 0.0087 0.0111
0.0 3.0 13881 nan 0.0165 0.0087 0.0111
0.0 4.0 18508 nan 0.0165 0.0087 0.0111
0.0 5.0 23135 nan 0.0165 0.0087 0.0111
0.0 6.0 27762 nan 0.0165 0.0087 0.0111
0.0 7.0 32389 nan 0.0165 0.0087 0.0111
0.0 8.0 37016 nan 0.0165 0.0087 0.0111
0.0 9.0 41643 nan 0.0165 0.0087 0.0111
0.0 10.0 46270 nan 0.0165 0.0087 0.0111
0.0 11.0 50897 nan 0.0165 0.0087 0.0111
0.0 12.0 55524 nan 0.0165 0.0087 0.0111
0.0 13.0 60151 nan 0.0165 0.0087 0.0111
0.0 14.0 64778 nan 0.0165 0.0087 0.0111
0.0 15.0 69405 nan 0.0165 0.0087 0.0111

Framework versions

  • Transformers 4.46.2
  • Pytorch 2.2.2
  • Datasets 2.16.1
  • Tokenizers 0.20.3