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bart-large-cnn-samsum-ElectrifAi_v6
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: 0.4591
- Rouge1: 70.5822
- Rouge2: 55.7529
- Rougel: 63.7452
- Rougelsum: 69.9659
- Gen Len: 113.6
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 | 20 | 0.7010 | 63.9182 | 44.7625 | 53.1206 | 63.0249 | 102.5 |
| No log | 2.0 | 40 | 0.5084 | 68.113 | 52.0277 | 60.5913 | 67.282 | 114.8 |
| No log | 3.0 | 60 | 0.4591 | 70.5822 | 55.7529 | 63.7452 | 69.9659 | 113.6 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.2
