bart-base-summarization-medical-47
This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1308
- Rouge1: 0.4191
- Rouge2: 0.2227
- Rougel: 0.3552
- Rougelsum: 0.3555
- Gen Len: 18.216
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: 3e-05
- train_batch_size: 4
- eval_batch_size: 1
- seed: 47
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- 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 | Gen Len |
---|---|---|---|---|---|---|---|---|
2.7197 | 1.0 | 1250 | 2.2012 | 0.4139 | 0.2191 | 0.3517 | 0.3522 | 17.835 |
2.6119 | 2.0 | 2500 | 2.1664 | 0.416 | 0.2218 | 0.3517 | 0.3519 | 18.075 |
2.5724 | 3.0 | 3750 | 2.1502 | 0.4162 | 0.2197 | 0.3522 | 0.3526 | 18.298 |
2.548 | 4.0 | 5000 | 2.1390 | 0.4144 | 0.2197 | 0.3509 | 0.3511 | 18.138 |
2.5441 | 5.0 | 6250 | 2.1296 | 0.4199 | 0.224 | 0.3558 | 0.356 | 18.267 |
2.5115 | 6.0 | 7500 | 2.1308 | 0.4191 | 0.2227 | 0.3552 | 0.3555 | 18.216 |
Framework versions
- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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