summarization_fine_tuning
This model is a fine-tuned version of facebook/bart-large-xsum on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.5474
- Rouge1: 53.215
- Rouge2: 28.4755
- Rougel: 43.9337
- Rougelsum: 48.5873
- Gen Len: 27.2592
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 |
|---|---|---|---|---|---|---|---|---|
| 1.3867 | 1.0 | 14732 | 1.6283 | 52.82 | 28.3657 | 43.6768 | 48.5632 | 27.1137 |
| 0.9705 | 2.0 | 29464 | 1.5474 | 53.215 | 28.4755 | 43.9337 | 48.5873 | 27.2592 |
| 0.5877 | 3.0 | 44196 | 1.7343 | 53.8648 | 28.8011 | 44.1837 | 49.2032 | 29.2225 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Base model
facebook/bart-large-xsum