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nl+no_processing

This model is a fine-tuned version of facebook/mbart-large-cc25 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6038
  • Smatch Precision: 73.7
  • Smatch Recall: 76.48
  • Smatch Fscore: 75.06
  • Smatch Unparsable: 0
  • Percent Not Recoverable: 0.2323

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: 2
  • eval_batch_size: 2
  • seed: 42
  • gradient_accumulation_steps: 8
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 25

Training results

Training Loss Epoch Step Validation Loss Smatch Precision Smatch Recall Smatch Fscore Smatch Unparsable Percent Not Recoverable
0.8025 1.0 3477 1.3793 18.51 65.71 28.88 0 0.0
0.13 2.0 6954 0.9377 27.0 71.3 39.16 0 0.1161
0.0953 3.0 10431 0.7509 34.09 72.74 46.42 0 0.1161
0.1386 4.0 13908 0.8524 33.38 73.32 45.87 2 0.0
0.0974 5.0 17385 0.6957 41.69 73.92 53.31 0 0.0
0.0705 6.0 20862 0.6145 47.98 75.12 58.55 0 0.0
0.2265 7.0 24339 0.6439 47.06 75.53 57.99 0 0.0
0.0506 8.0 27817 0.5974 53.0 76.95 62.77 0 0.0
0.064 9.0 31294 0.6387 51.83 77.47 62.11 0 0.0
0.0112 10.0 34771 0.6066 54.82 76.98 64.03 0 0.0
0.047 11.0 38248 0.5970 60.36 77.04 67.69 0 0.0
0.0134 12.0 41725 0.5675 61.72 77.15 68.58 0 0.0
0.0656 13.0 45202 0.6210 62.8 76.92 69.15 0 0.0581
0.015 14.0 48679 0.6257 62.8 77.32 69.31 0 0.0
0.0134 15.0 52156 0.5635 66.7 77.34 71.63 0 0.1161
0.0265 16.0 55634 0.5839 67.61 76.76 71.89 0 0.0581
0.0219 17.0 59111 0.5894 68.66 77.43 72.78 0 0.1161
0.0008 18.0 62588 0.5981 68.44 77.57 72.72 0 0.0
0.0157 19.0 66065 0.6184 69.88 77.42 73.46 0 0.0581
0.0334 20.0 69542 0.6026 70.76 77.37 73.92 0 0.2323
0.0619 21.0 73019 0.6021 72.03 77.0 74.44 0 0.1742
0.0075 22.0 76496 0.6166 72.33 76.74 74.47 0 0.0581
0.0164 23.0 79973 0.6100 72.75 77.03 74.83 0 0.2323
0.0011 24.0 83451 0.6037 73.7 76.51 75.08 0 0.2323
0.0865 25.0 86925 0.6038 73.7 76.48 75.06 0 0.2323

Framework versions

  • Transformers 4.34.0.dev0
  • Pytorch 2.0.1+cu117
  • Datasets 2.14.2
  • Tokenizers 0.13.3
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