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fine_tuned_bart

This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.7075

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: 4e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 64
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss
No log 1.0 8 0.7205
0.4729 2.0 16 0.7109
0.4794 3.0 24 0.7048
0.4716 4.0 32 0.7081
0.476 5.0 40 0.7095
0.476 6.0 48 0.7174
0.4751 7.0 56 0.7050
0.4683 8.0 64 0.7047
0.4583 9.0 72 0.7058
0.474 10.0 80 0.7045
0.474 11.0 88 0.7062
0.4651 12.0 96 0.7047
0.4523 13.0 104 0.7028
0.4626 14.0 112 0.7049
0.4634 15.0 120 0.7067
0.4634 16.0 128 0.7091
0.4543 17.0 136 0.7087
0.4502 18.0 144 0.7084
0.4604 19.0 152 0.7098
0.4503 20.0 160 0.7065
0.4503 21.0 168 0.7046
0.4642 22.0 176 0.7033
0.4334 23.0 184 0.7029
0.4626 24.0 192 0.7037
0.4584 25.0 200 0.7046
0.4584 26.0 208 0.7063
0.4508 27.0 216 0.7075
0.4498 28.0 224 0.7078
0.4532 29.0 232 0.7077
0.4514 30.0 240 0.7075

Framework versions

  • PEFT 0.12.0
  • Transformers 4.42.4
  • Pytorch 2.3.1+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1
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