tidy-tab-model

This model is a fine-tuned version of google-t5/t5-small on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 3.5060
  • Rouge1: 0.3341
  • Rouge2: 0.1528
  • Rougel: 0.3104
  • Rougelsum: 0.3125
  • Gen Len: 17.75

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: 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: 8
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 7 4.4385 0.1922 0.0928 0.1885 0.1862 17.9167
No log 2.0 14 4.1803 0.2265 0.1136 0.2229 0.2214 17.75
No log 3.0 21 3.9826 0.2505 0.0972 0.2495 0.2517 17.1667
No log 4.0 28 3.8140 0.3166 0.131 0.3117 0.3168 17.5
No log 5.0 35 3.6817 0.3442 0.1594 0.3194 0.3211 17.4167
No log 6.0 42 3.5924 0.3341 0.1528 0.3104 0.3125 17.75
No log 7.0 49 3.5356 0.3341 0.1528 0.3104 0.3125 17.75
No log 8.0 56 3.5060 0.3341 0.1528 0.3104 0.3125 17.75

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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