results

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

  • eval_loss: 0.0001
  • eval_model_preparation_time: 0.0049
  • eval_rouge1: 99.9541
  • eval_rouge2: 87.8299
  • eval_rougeL: 99.9541
  • eval_rougeLsum: 99.9541
  • eval_runtime: 2.9907
  • eval_samples_per_second: 22.068
  • eval_steps_per_second: 3.009
  • step: 0

Model description

We have fine tuned google/mt5-small model on xonic48 amazon review data

Intended uses & limitations

More information needed

Training and evaluation data

We reduced the dataset to 20%, and selected data in english language, and then filtered it for book reviews.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • 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: 3

Framework versions

  • Transformers 4.46.3
  • Pytorch 2.5.1+cu121
  • Datasets 3.1.0
  • Tokenizers 0.20.3
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