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bart-large-cnn-ing-extraction-e4
This model is a fine-tuned version of facebook/bart-large-cnn on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.6226
- Rouge1: 10.8186
- Rouge2: 4.3032
- Rougel: 10.7802
- Rougelsum: 10.7952
- Gen Len: 57.5739
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 |
|---|---|---|---|---|---|---|---|---|
| 0.6235 | 1.0 | 762 | 3.1458 | 14.9141 | 5.5712 | 14.7529 | 14.8292 | 57.6903 |
| 0.2435 | 2.0 | 1524 | 2.2255 | 6.4408 | 2.4546 | 6.4219 | 6.4393 | 57.2955 |
| 0.1467 | 3.0 | 2286 | 2.9673 | 9.9243 | 3.9008 | 9.932 | 9.9268 | 57.6506 |
| 0.0627 | 4.0 | 3048 | 2.6226 | 10.8186 | 4.3032 | 10.7802 | 10.7952 | 57.5739 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
