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metadata
base_model: hiba2/results_arat5-2_wiki
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: results_arat5-3_wiki
    results: []

results_arat5-3_wiki

This model is a fine-tuned version of hiba2/results_arat5-2_wiki on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.7821
  • Rouge1: 0.0926
  • Rouge2: 0.0015
  • Rougel: 0.0934
  • Rougelsum: 0.0928
  • Gen Len: 19.0

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: 4
  • eval_batch_size: 4
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 20

Training results

Training Loss Epoch Step Gen Len Validation Loss Rouge1 Rouge2 Rougel Rougelsum
7.8936 0.9506 500 0.0 5.9107 0.0 0.0 0.0 0.0
5.5649 1.9011 1000 18.8876 4.9336 0.0905 0.0 0.0915 0.0912
4.9098 2.8517 1500 18.8989 4.3731 0.0905 0.0 0.0915 0.0912
4.4486 3.8023 2000 19.0 3.9340 0.0875 0.0 0.0885 0.0882
4.0755 4.7529 2500 18.9382 3.5412 0.0881 0.0 0.0891 0.0887
3.6998 5.7034 3000 18.8783 3.1344 0.095 0.0002 0.0958 0.0954
3.3129 6.6540 3500 18.8408 2.8528 0.0935 0.0013 0.0945 0.094
3.1053 7.6046 4000 18.9382 2.6196 0.0936 0.0008 0.0946 0.0941
2.8412 8.5551 4500 18.867 2.4414 0.091 0.0011 0.0919 0.0915
2.702 9.5057 5000 18.8783 2.2952 0.0936 0.001 0.0948 0.0946
2.5611 10.4563 5500 19.0 2.1816 0.093 0.0011 0.0941 0.0936
2.4499 11.4068 6000 18.8502 2.0914 0.0988 0.0011 0.0995 0.099
2.3764 12.3574 6500 18.8371 2.0264 0.0992 0.0016 0.0997 0.0995
2.3172 13.3080 7000 18.9888 1.9853 0.098 0.0015 0.099 0.0986
2.2794 14.2586 7500 18.9888 1.9615 0.0971 0.0023 0.0977 0.0976
2.2178 15.2091 8000 1.9424 0.0961 0.0009 0.0972 0.0968 19.0
2.2378 16.1597 8500 1.8855 0.0935 0.0011 0.0942 0.0937 19.0
2.1573 17.1103 9000 1.8386 0.0952 0.0009 0.0962 0.0958 19.0
2.132 18.0608 9500 1.8055 0.0919 0.0012 0.0929 0.0923 18.8783
2.1035 19.0114 10000 1.7863 0.0942 0.0015 0.0949 0.0945 19.0
2.0818 19.9620 10500 1.7821 0.0926 0.0015 0.0934 0.0928 19.0

Framework versions

  • Transformers 4.42.0.dev0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1