metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: distilbart-cnn-12-6-summarization_final_labeled_data
results: []
distilbart-cnn-12-6-summarization_final_labeled_data
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: 0.0858
- Rouge1: 76.5974
- Rouge2: 66.1659
- Rougel: 71.9284
- Rougelsum: 75.2459
- Gen Len: 122.5
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 | 0.2852 | 61.0841 | 45.81 | 52.9835 | 59.0452 | 116.92 |
| No log | 2.0 | 198 | 0.1547 | 71.534 | 59.9905 | 66.4697 | 70.5213 | 117.56 |
| No log | 3.0 | 297 | 0.1100 | 71.6464 | 59.0112 | 67.3835 | 70.5206 | 117.24 |
| No log | 4.0 | 396 | 0.0960 | 77.9213 | 67.6116 | 73.7888 | 76.8473 | 123.62 |
| No log | 5.0 | 495 | 0.0858 | 76.5974 | 66.1659 | 71.9284 | 75.2459 | 122.5 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1