Natet's picture
Update README.md
48ed33c
|
raw
history blame
2.07 kB
metadata
license: apache-2.0
base_model: IlyaGusev/rut5_base_sum_gazeta
tags:
  - summarization_4
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: rut5_base_sum_gazeta-finetuned_week_gpt
    results: []

rut5_base_sum_gazeta-finetuned_week_gpt

This model is a fine-tuned version of IlyaGusev/rut5_base_sum_gazeta on Natet/gpt_week_yandex dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2643
  • Rouge1: 38.9266
  • Rouge2: 18.0587
  • Rougel: 38.1447
  • Rougelsum: 38.1337

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: 5.6e-05
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 8

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
1.7691 1.0 1110 1.4005 37.7689 17.7394 36.8468 36.8842
1.4892 2.0 2220 1.3477 35.9349 16.8403 35.1786 35.2055
1.3579 3.0 3330 1.3079 37.7579 17.6421 36.8439 36.8182
1.2708 4.0 4440 1.2675 37.867 17.3909 36.9706 36.987
1.2006 5.0 5550 1.2703 38.8218 17.9772 38.001 37.9811
1.1519 6.0 6660 1.2703 38.0351 17.5386 37.209 37.1815
1.1132 7.0 7770 1.2593 38.4673 17.8343 37.529 37.5268
1.0932 8.0 8880 1.2643 38.9266 18.0587 38.1447 38.1337

Framework versions

  • Transformers 4.33.0
  • Pytorch 2.0.0
  • Datasets 2.1.0
  • Tokenizers 0.13.3