metadata

license: mit
base_model: facebook/bart-large-cnn
tags:
  - generated_from_trainer
datasets:
  - cnn_dailymail
metrics:
  - rouge
model-index:
  - name: bart-large-cnn-finetuned-CNN-ML
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: cnn_dailymail
          type: cnn_dailymail
          config: 3.0.0
          split: test
          args: 3.0.0
        metrics:
          - name: Rouge1
            type: rouge
            value: 44.4382

bart-large-cnn-finetuned-CNN-ML

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

Loss: 2.1137
Rouge1: 44.4382
Rouge2: 20.686
Rougel: 29.9355
Rougelsum: 41.4113
Gen Len: 93.846

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: 2
eval_batch_size: 2
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.0341	1.0	1000	1.5412	43.0331	20.1656	29.6298	39.9858	83.22
0.6416	2.0	2000	1.8461	44.2294	20.5043	29.6298	41.1457	93.366
0.3766	3.0	3000	2.1137	44.4382	20.686	29.9355	41.4113	93.846

Framework versions

Transformers 4.33.1
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3