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bart-large-cnn-samsum-ElectrifAi_v8.3
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: 0.8755
- Rouge1: 60.4165
- Rouge2: 41.6463
- Rougel: 50.9083
- Rougelsum: 59.2499
- Gen Len: 109.7
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 | 0.9037 | 57.105 | 36.4038 | 46.3683 | 55.8701 | 99.15 |
| No log | 2.0 | 40 | 0.8759 | 58.7016 | 39.3877 | 47.444 | 57.4063 | 113.8 |
| No log | 3.0 | 60 | 0.8755 | 60.4165 | 41.6463 | 50.9083 | 59.2499 | 109.7 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.12.1
- Datasets 2.6.1
- Tokenizers 0.13.2
