tst-summarization
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: 1.9975
- Rouge1: 56.239
- Rouge2: 28.9873
- Rougel: 38.5242
- Rougelsum: 53.7902
- Gen Len: 105.2973
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Framework versions
- Transformers 4.18.0.dev0
- Pytorch 1.10.0
- Datasets 1.18.4
- Tokenizers 0.11.6
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