metadata

license: apache-2.0
base_model: sshleifer/distilbart-cnn-6-6
tags:
  - generated_from_trainer
datasets:
  - wcep-10
metrics:
  - rouge
model-index:
  - name: thesis-bart-finetuned-on-original-wcep
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: wcep-10
          type: wcep-10
          config: roberta
          split: validation
          args: roberta
        metrics:
          - name: Rouge1
            type: rouge
            value: 37.1938

thesis-bart-finetuned-on-original-wcep

This model is a fine-tuned version of sshleifer/distilbart-cnn-6-6 on the wcep-10 dataset. It achieves the following results on the evaluation set:

Loss: 1.9981
Rouge1: 37.1938
Rouge2: 16.5385
Rougel: 26.7997
Rougelsum: 30.3278
Gen Len: 67.5627

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: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.0801	1.0	510	2.0119	36.476	16.0059	26.3489	29.7099	67.9882
1.7597	2.0	1020	1.9868	36.9333	16.3738	26.5067	30.1156	68.3961
1.5997	3.0	1530	1.9981	37.1938	16.5385	26.7997	30.3278	67.5627

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2