metadata

license: apache-2.0
base_model: sshleifer/distilbart-cnn-12-6
tags:
  - generated_from_trainer
datasets:
  - dialogstudio
metrics:
  - rouge
model-index:
  - name: my_awesome_billsum_model
    results:
      - task:
          name: Sequence-to-sequence Language Modeling
          type: text2text-generation
        dataset:
          name: dialogstudio
          type: dialogstudio
          config: TweetSumm
          split: test
          args: TweetSumm
        metrics:
          - name: Rouge1
            type: rouge
            value: 0.4187

my_awesome_billsum_model

This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on the dialogstudio dataset. It achieves the following results on the evaluation set:

Loss: 1.9811
Rouge1: 0.4187
Rouge2: 0.1911
Rougel: 0.3373
Rougelsum: 0.338
Gen Len: 65.1636

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: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	55	2.0591	0.4232	0.1899	0.3412	0.342	64.8545
No log	2.0	110	1.9802	0.4125	0.19	0.3329	0.3334	66.7545
No log	3.0	165	1.9671	0.4172	0.1927	0.3348	0.3357	65.3545
No log	4.0	220	1.9811	0.4187	0.1911	0.3373	0.338	65.1636

Framework versions

Transformers 4.41.1
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1