bart-med-term-conditional-masking-0
This model is a fine-tuned version of facebook/bart-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5041
- Rouge2 Precision: 0.7497
- Rouge2 Recall: 0.5246
- Rouge2 Fmeasure: 0.5986
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: 4
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge2 Precision | Rouge2 Recall | Rouge2 Fmeasure |
---|---|---|---|---|---|---|
0.6381 | 1.0 | 13915 | 0.5595 | 0.734 | 0.5152 | 0.5873 |
0.5429 | 2.0 | 27830 | 0.5243 | 0.7441 | 0.5225 | 0.5956 |
0.5002 | 3.0 | 41745 | 0.5078 | 0.7482 | 0.5238 | 0.5976 |
0.4607 | 4.0 | 55660 | 0.5041 | 0.7497 | 0.5246 | 0.5986 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6
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