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bart-large-cnn-samsum-ElectrifAi_v10
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: 1.1748
- Rouge1: 58.3392
- Rouge2: 35.1686
- Rougel: 45.4136
- Rougelsum: 56.9138
- Gen Len: 108.375
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 | 21 | 1.1573 | 56.0772 | 34.1572 | 44.3652 | 54.8621 | 106.0833 |
| No log | 2.0 | 42 | 1.1764 | 57.7245 | 34.6517 | 45.67 | 56.3426 | 106.4167 |
| No log | 3.0 | 63 | 1.1748 | 58.3392 | 35.1686 | 45.4136 | 56.9138 | 108.375 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.2
