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story_summarizer-finetuned
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: 2.9028
- Rouge1: 30.4344
- Rouge2: 6.2601
- Rougel: 18.9971
- Rougelsum: 26.4496
- Gen Len: 95.0942
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: 8
- eval_batch_size: 8
- 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 | 150 | 2.8526 | 29.1919 | 5.8045 | 18.2639 | 25.4635 | 102.0117 |
No log | 2.0 | 300 | 2.8654 | 30.0355 | 6.0614 | 18.7598 | 26.1234 | 96.4292 |
No log | 3.0 | 450 | 2.9028 | 30.4344 | 6.2601 | 18.9971 | 26.4496 | 95.0942 |
Framework versions
- Transformers 4.27.4
- Pytorch 2.0.0+cu118
- Datasets 2.11.0
- Tokenizers 0.13.2