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bart-large-cnn-samsum-ElectrifAi_v13
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: 2.9198
- Rouge1: 46.6683
- Rouge2: 22.3077
- Rougel: 37.436
- Rougelsum: 44.2797
- Gen Len: 86.6
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 | 10 | 3.0963 | 46.6161 | 24.9843 | 36.3484 | 42.7551 | 81.4 |
| No log | 2.0 | 20 | 2.9398 | 49.7463 | 23.695 | 36.3679 | 45.2876 | 84.6 |
| No log | 3.0 | 30 | 2.9198 | 46.6683 | 22.3077 | 37.436 | 44.2797 | 86.6 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
