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模型:
Qiliang/distilbart-xsum-12-3-whole_summary_chatGPT_and_tweetsum
任务:
文生文
许可:
apache-2.0
中文distilbart-xsum-12-3-whole_summary_chatGPT_and_tweetsum
This model is a fine-tuned version of sshleifer/distilbart-xsum-12-3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.7952
- Rouge1: 45.7353
- Rouge2: 29.1566
- Rougel: 45.8429
- Rougelsum: 45.7353
- Gen Len: 16.6
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 397 | 2.8069 | 42.233 | 23.7538 | 39.2701 | 39.2701 | 17.0 |
| 2.8673 | 2.0 | 794 | 2.7736 | 48.2389 | 29.6927 | 43.5004 | 43.5004 | 17.4 |
| 1.8043 | 3.0 | 1191 | 2.7952 | 45.7353 | 29.1566 | 45.8429 | 45.7353 | 16.6 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.12.1