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metadata
license: apache-2.0
base_model: facebook/bart-base
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: BARTModel_ExerciseLog
    results: []

BARTModel_ExerciseLog

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

  • Loss: 4.3574
  • Rouge1: 0.8531
  • Rouge2: 0.581
  • Rougel: 0.8531
  • Rougelsum: 0.8531
  • Gen Len: 7.2857

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: 16
  • eval_batch_size: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 18

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 2 7.5886 0.4437 0.1117 0.4458 0.4459 16.5714
No log 2.0 4 6.4463 0.4127 0.1117 0.4136 0.4155 16.0
No log 3.0 6 5.9474 0.5136 0.0952 0.5102 0.5204 8.2857
No log 4.0 8 5.6884 0.5537 0.2381 0.5459 0.5459 8.0
No log 5.0 10 5.5303 0.55 0.2381 0.5452 0.5452 6.5714
No log 6.0 12 5.4149 0.55 0.2381 0.5452 0.5452 6.7143
No log 7.0 14 5.2489 0.5286 0.2 0.5197 0.5197 7.0
No log 8.0 16 5.0956 0.5388 0.2 0.5286 0.5286 7.0
No log 9.0 18 4.9528 0.5388 0.2 0.5286 0.5286 7.0
No log 10.0 20 4.8291 0.5388 0.2 0.5286 0.5286 7.1429
No log 11.0 22 4.7158 0.5748 0.2714 0.567 0.5667 7.4286
No log 12.0 24 4.6173 0.7388 0.3429 0.7388 0.7388 7.2857
No log 13.0 26 4.5333 0.8531 0.581 0.8531 0.8531 7.2857
No log 14.0 28 4.4660 0.8531 0.581 0.8531 0.8531 7.2857
No log 15.0 30 4.4177 0.8531 0.581 0.8531 0.8531 7.2857
No log 16.0 32 4.3857 0.8531 0.581 0.8531 0.8531 7.2857
No log 17.0 34 4.3660 0.8531 0.581 0.8531 0.8531 7.2857
No log 18.0 36 4.3574 0.8531 0.581 0.8531 0.8531 7.2857

Framework versions

  • Transformers 4.41.2
  • Pytorch 2.3.0+cu121
  • Datasets 2.20.0
  • Tokenizers 0.19.1