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bart-large-cnn-samsum-icsi-ami-v3
This model is a fine-tuned version of philschmid/bart-large-cnn-samsum on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.2328
- Rouge1: 39.9389
- Rouge2: 12.2256
- Rougel: 23.4739
- Rougelsum: 36.7757
- Gen Len: 155.3529
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: 5e-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 | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 135 | 3.2655 | 38.2358 | 11.9547 | 23.1235 | 35.1978 | 163.8824 |
| No log | 2.0 | 270 | 3.2328 | 39.9389 | 12.2256 | 23.4739 | 36.7757 | 155.3529 |
| No log | 3.0 | 405 | 3.4852 | 40.8728 | 11.6505 | 22.8143 | 37.3518 | 144.7647 |
| 2.1798 | 4.0 | 540 | 4.0977 | 40.3307 | 10.4437 | 22.6059 | 36.2414 | 135.1471 |
| 2.1798 | 5.0 | 675 | 4.6537 | 41.2432 | 10.7188 | 22.7868 | 37.3837 | 136.1471 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.10.1
- Tokenizers 0.13.2
