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bart-large-finetuned-summarization
This model is a fine-tuned version of facebook/bart-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.1841
- Rouge1: 32.6763
- Rouge2: 23.1598
- Rougel: 31.2322
- Rougelsum: 32.278
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: 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 1.7048 | 1.0 | 308 | 1.1916 | 32.0296 | 21.6931 | 30.2623 | 31.1959 |
| 1.1153 | 2.0 | 616 | 1.2054 | 30.7076 | 21.7771 | 29.3115 | 29.9377 |
| 0.78 | 3.0 | 924 | 1.1096 | 32.4164 | 22.494 | 31.0367 | 31.8135 |
| 0.5335 | 4.0 | 1232 | 1.1547 | 33.2561 | 23.6119 | 32.1371 | 32.591 |
| 0.361 | 5.0 | 1540 | 1.1841 | 32.6763 | 23.1598 | 31.2322 | 32.278 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
