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LED-Base-NSPCC

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metadata
license: apache-2.0
base_model: allenai/led-base-16384
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: LED-Base-NSPCC
    results: []

LED-Base-NSPCC

This model is a fine-tuned version of allenai/led-base-16384 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.8734
  • Rouge1: 0.4910
  • Rouge2: 0.2207
  • Rougel: 0.2847
  • Rougelsum: 0.2840

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: 0.0003
  • train_batch_size: 4
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.03
  • num_epochs: 4
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum
2.4662 0.9947 47 1.9451 0.4528 0.1809 0.2560 0.2558
1.6508 1.9894 94 1.8497 0.4889 0.2146 0.2720 0.2716
1.2549 2.9841 141 1.8268 0.4812 0.2092 0.2756 0.2753
0.9955 3.9788 188 1.8734 0.4910 0.2207 0.2847 0.2840

Framework versions

  • Transformers 4.40.1
  • Pytorch 2.2.1+cu121
  • Datasets 2.19.0
  • Tokenizers 0.19.1