thesis-bart-finetuned-on-original-wcep
This model is a fine-tuned version of sshleifer/distilbart-cnn-6-6 on the wcep-10 dataset. It achieves the following results on the evaluation set:
- Loss: 1.9981
- Rouge1: 37.2224
- Rouge2: 16.5575
- Rougel: 26.7904
- Rougelsum: 30.3497
- Gen Len: 67.5627
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: 16
- eval_batch_size: 16
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.0801 | 1.0 | 510 | 2.0119 | 36.4915 | 16.0165 | 26.3565 | 29.7397 | 67.9882 |
| 1.7597 | 2.0 | 1020 | 1.9868 | 36.9513 | 16.3776 | 26.4974 | 30.1234 | 68.3961 |
| 1.5997 | 3.0 | 1530 | 1.9981 | 37.2224 | 16.5575 | 26.7904 | 30.3497 | 67.5627 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for roofdancer/thesis-bart-finetuned-on-original-wcep
Base model
sshleifer/distilbart-cnn-6-6