bart-large-xsumfinetuned-samsum
This model is a fine-tuned version of facebook/bart-large-cnn on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9976
- Rouge1: 0.4246
- Rouge2: 0.2069
- Rougel: 0.3253
- Rougelsum: 0.3907
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: 6
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
0.2858 | 1.0 | 3683 | 2.3127 | 0.4051 | 0.1926 | 0.3072 | 0.3720 |
0.3128 | 2.0 | 7366 | 2.3467 | 0.4007 | 0.1911 | 0.3037 | 0.3687 |
0.2544 | 3.0 | 11049 | 2.3126 | 0.4145 | 0.2019 | 0.3159 | 0.3801 |
0.1846 | 4.0 | 14732 | 2.6484 | 0.4088 | 0.1977 | 0.3096 | 0.3774 |
0.1143 | 5.0 | 18415 | 2.7793 | 0.4173 | 0.1997 | 0.3155 | 0.3843 |
0.0687 | 6.0 | 22098 | 2.9976 | 0.4246 | 0.2069 | 0.3253 | 0.3907 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Base model
facebook/bart-large-cnn