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distilbart-cnn-12-6-sec
This model is a fine-tuned version of sshleifer/distilbart-cnn-12-6 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1379
- Rouge1: 72.2845
- Rouge2: 61.1501
- Rougel: 67.6999
- Rougelsum: 70.9968
- Gen Len: 113.8
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: 2
- eval_batch_size: 2
- 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 | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 99 | 0.4429 | 56.0806 | 40.5969 | 47.5271 | 53.7227 | 115.44 |
| No log | 2.0 | 198 | 0.2279 | 56.6042 | 42.1781 | 48.9542 | 54.951 | 116.84 |
| No log | 3.0 | 297 | 0.1845 | 65.9646 | 51.8575 | 59.8647 | 64.103 | 113.8 |
| No log | 4.0 | 396 | 0.1532 | 71.6132 | 61.1434 | 67.4165 | 70.4093 | 110.46 |
| No log | 5.0 | 495 | 0.1379 | 72.2845 | 61.1501 | 67.6999 | 70.9968 | 113.8 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
