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-old
results: []
bert-small2bert-small-finetuned-cnn_daily_mail-summarization-finetuned-bbc-news-old
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: 0.6733
- Rouge1: 60.9431
- Rouge2: 49.8688
- Rougel: 42.4663
- Rougelsum: 59.836
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 |
|---|---|---|---|---|---|---|---|
| 0.8246 | 1.0 | 223 | 0.6974 | 55.2742 | 41.9883 | 37.8584 | 53.7602 |
| 0.6396 | 2.0 | 446 | 0.6786 | 56.0006 | 43.1917 | 38.5125 | 54.4571 |
| 0.5582 | 3.0 | 669 | 0.6720 | 57.8912 | 45.7807 | 40.0807 | 56.4985 |
| 0.505 | 4.0 | 892 | 0.6659 | 59.6611 | 48.0095 | 41.752 | 58.5059 |
| 0.4611 | 5.0 | 1115 | 0.6706 | 59.7241 | 48.164 | 41.4523 | 58.5295 |
| 0.4254 | 6.0 | 1338 | 0.6711 | 59.8524 | 48.1821 | 41.2299 | 58.6072 |
| 0.3967 | 7.0 | 1561 | 0.6718 | 60.3009 | 49.0085 | 42.0306 | 59.0723 |
| 0.38 | 8.0 | 1784 | 0.6733 | 60.9431 | 49.8688 | 42.4663 | 59.836 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1