metadata
license: apache-2.0
tags:
- summarisation
- generated_from_trainer
metrics:
- rouge
model-index:
- name: >-
bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-Sumy
results: []
bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-Sumy
This model is a fine-tuned version of mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5583
- Rouge1: 55.2899
- Rouge2: 43.2426
- Rougel: 38.5056
- Rougelsum: 53.8807
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: 5.6e-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: 8
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.7407 | 1.0 | 223 | 1.5900 | 51.3058 | 38.3952 | 35.7343 | 49.7129 |
| 1.4813 | 2.0 | 446 | 1.5500 | 53.8089 | 41.2455 | 37.3864 | 52.3387 |
| 1.3517 | 3.0 | 669 | 1.5429 | 53.4914 | 40.907 | 37.1428 | 52.0338 |
| 1.2432 | 4.0 | 892 | 1.5472 | 54.1139 | 41.3589 | 37.6392 | 52.711 |
| 1.1748 | 5.0 | 1115 | 1.5426 | 55.3482 | 43.312 | 38.0625 | 54.0424 |
| 1.1108 | 6.0 | 1338 | 1.5529 | 55.4752 | 43.3561 | 38.5813 | 54.1141 |
| 1.0745 | 7.0 | 1561 | 1.5539 | 55.705 | 43.6772 | 38.7629 | 54.3892 |
| 1.0428 | 8.0 | 1784 | 1.5583 | 55.2899 | 43.2426 | 38.5056 | 53.8807 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1