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bart-large-cnn-samsum-ElectrifAi_v9
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: 1.2325
- Rouge1: 55.1928
- Rouge2: 33.3871
- Rougel: 43.865
- Rougelsum: 54.1984
- Gen Len: 108.8667
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: 4
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 27 | 1.2252 | 55.969 | 34.0884 | 43.1389 | 54.7972 | 108.0 |
| No log | 2.0 | 54 | 1.2156 | 55.834 | 34.3509 | 43.5382 | 54.4829 | 102.8 |
| No log | 3.0 | 81 | 1.2325 | 55.1928 | 33.3871 | 43.865 | 54.1984 | 108.8667 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.2
