metadata
license: apache-2.0
base_model: sshleifer/distilbart-cnn-12-6
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: distilbart-12-6-cnn-dm-abstractive-summarizer
results: []
distilbart-12-6-cnn-dm-abstractive-summarizer
This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6988
- Rouge1: 0.42
- Rouge2: 0.2006
- Rougel: 0.3032
- Rougelsum: 0.3033
- Generated Length: 72.6006
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Generated Length |
|---|---|---|---|---|---|---|---|---|
| 1.1498 | 1.0 | 1436 | 1.5556 | 0.4009 | 0.1815 | 0.2843 | 0.2843 | 72.1027 |
| 1.1051 | 2.0 | 2872 | 1.5456 | 0.4127 | 0.191 | 0.2941 | 0.2942 | 71.2483 |
| 0.892 | 3.0 | 4308 | 1.5954 | 0.4129 | 0.1924 | 0.2946 | 0.2947 | 72.453 |
| 0.7543 | 4.0 | 5744 | 1.6574 | 0.4177 | 0.1974 | 0.3018 | 0.3017 | 71.8179 |
| 0.651 | 5.0 | 7180 | 1.6988 | 0.42 | 0.2006 | 0.3032 | 0.3033 | 72.6006 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2