my_awesome_billsum_model
This model is a fine-tuned version of facebook/bart-large-cnn on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 1.4680
- Rouge1: 0.5281
- Rouge2: 0.2775
- Rougel: 0.3421
- Rougelsum: 0.4021
- Gen Len: 130.3669
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: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
---|---|---|---|---|---|---|---|---|
No log | 1.0 | 495 | 1.5156 | 0.5029 | 0.2538 | 0.3184 | 0.3865 | 131.4073 |
1.8254 | 2.0 | 990 | 1.4455 | 0.5102 | 0.2663 | 0.3395 | 0.3949 | 117.4516 |
1.2925 | 3.0 | 1485 | 1.4291 | 0.5212 | 0.2713 | 0.3392 | 0.3944 | 130.379 |
0.9936 | 4.0 | 1980 | 1.4680 | 0.5281 | 0.2775 | 0.3421 | 0.4021 | 130.3669 |
Framework versions
- Transformers 4.27.3
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2
- Downloads last month
- 4
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.