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mt5_deed_sum_1

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metadata
license: apache-2.0
base_model: google/mt5-base
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: mt5_deed_sum_1
    results: []

mt5_deed_sum_1

This model is a fine-tuned version of google/mt5-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.5951
  • Rouge1: 0.0572
  • Rouge2: 0.0
  • Rougel: 0.0572
  • Rougelsum: 0.0572
  • 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: 2e-05
  • train_batch_size: 2
  • eval_batch_size: 2
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 5000
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
24.1526 1.0 375 15.7524 0.7082 0.0 0.6842 0.6883 12.0881
11.2879 2.0 750 13.1581 0.7082 0.0 0.6842 0.6883 12.3208
10.5585 3.0 1125 7.4334 0.7082 0.0 0.6842 0.6883 17.1384
2.9668 4.0 1500 6.5357 0.7487 0.0 0.7176 0.7257 19.0
3.7198 5.0 1875 2.1303 0.7487 0.0 0.7176 0.7257 19.0
1.3383 6.0 2250 1.8675 0.7487 0.0 0.7176 0.7257 19.0
3.4973 7.0 2625 1.6299 0.7487 0.0 0.7176 0.7257 18.8994
11.7006 8.0 3000 4.6990 0.7487 0.0 0.7176 0.7257 19.0
0.4529 9.0 3375 1.0729 0.7487 0.0 0.7176 0.7257 19.0
1.2783 10.0 3750 0.9424 0.7487 0.0 0.7176 0.7257 19.0
0.7953 11.0 4125 0.8889 1.0108 0.2013 0.892 0.9014 19.0
0.9359 12.0 4500 0.7996 1.1489 0.3019 0.9952 0.9877 19.0
0.5759 13.0 4875 0.7622 0.1572 0.1144 0.1572 0.1572 19.0
0.1533 14.0 5250 0.7068 0.2144 0.1144 0.1715 0.1715 19.0
0.4524 15.0 5625 0.6760 0.3145 0.2287 0.3145 0.3145 19.0
1.0126 16.0 6000 0.6627 0.0 0.0 0.0 0.0 19.0
0.1065 17.0 6375 0.6391 0.3145 0.2287 0.3145 0.3145 19.0
0.2096 18.0 6750 0.6419 0.2144 0.1144 0.2144 0.2144 19.0
0.5649 19.0 7125 0.6261 0.1572 0.1144 0.1572 0.1572 19.0
0.125 20.0 7500 0.6139 0.1572 0.1144 0.1572 0.1572 19.0
0.5511 21.0 7875 0.6057 0.3145 0.2287 0.3145 0.3145 19.0
0.0759 22.0 8250 0.6029 0.3145 0.2287 0.3145 0.3145 19.0
0.3491 23.0 8625 0.5995 0.3145 0.2287 0.3145 0.3145 19.0
0.3735 24.0 9000 0.5936 0.1572 0.1144 0.1572 0.1572 19.0
0.3451 25.0 9375 0.5951 0.0572 0.0 0.0572 0.0572 19.0

Framework versions

  • Transformers 4.37.2
  • Pytorch 2.1.0.dev20230811+cu121
  • Datasets 2.17.0
  • Tokenizers 0.15.2