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bart-large-cnn-samsum-ElectrifAi_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: 0.8053
- Rouge1: 62.0348
- Rouge2: 41.9592
- Rougel: 49.1046
- Rougelsum: 59.4965
- Gen Len: 101.2747
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 | 23 | 1.1760 | 54.8264 | 32.0931 | 40.5826 | 52.2503 | 99.4505 |
| No log | 2.0 | 46 | 0.9005 | 59.7325 | 38.3487 | 45.8861 | 56.9922 | 108.3846 |
| No log | 3.0 | 69 | 0.8053 | 62.0348 | 41.9592 | 49.1046 | 59.4965 | 101.2747 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.2
