bart-base-samsum
This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5834
- Rouge1: 47.552
- Rouge2: 24.8542
- Rougel: 40.56
- Rougelsum: 44.3423
- Gen Len: 17.8337
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: 8e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- 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 |
---|---|---|---|---|---|---|---|---|
1.8884 | 1.0 | 1841 | 1.6325 | 47.0402 | 24.1542 | 39.6427 | 43.8472 | 18.5941 |
1.5081 | 2.0 | 3683 | 1.5834 | 47.552 | 24.8542 | 40.56 | 44.3423 | 17.8337 |
1.2216 | 3.0 | 5524 | 1.5855 | 48.2058 | 25.1623 | 40.9023 | 44.2822 | 17.901 |
1.0074 | 4.0 | 7366 | 1.6049 | 48.3145 | 25.2348 | 40.8688 | 44.4735 | 18.4829 |
0.8544 | 5.0 | 9205 | 1.6455 | 48.5926 | 25.3142 | 40.9144 | 44.6577 | 18.3924 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
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facebook/bart-base