bart-base-summarization-medical-51
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: 2.1339
- Rouge1: 0.4189
- Rouge2: 0.2237
- Rougel: 0.356
- Rougelsum: 0.3558
- Gen Len: 18.191
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: 51
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.7175 | 1.0 | 1250 | 2.2013 | 0.4107 | 0.219 | 0.35 | 0.3496 | 17.772 |
| 2.5872 | 2.0 | 2500 | 2.1674 | 0.4158 | 0.2228 | 0.3536 | 0.3531 | 18.005 |
| 2.5979 | 3.0 | 3750 | 2.1502 | 0.415 | 0.2215 | 0.351 | 0.3509 | 18.111 |
| 2.5579 | 4.0 | 5000 | 2.1428 | 0.4178 | 0.226 | 0.3548 | 0.3549 | 18.143 |
| 2.5332 | 5.0 | 6250 | 2.1350 | 0.4172 | 0.2243 | 0.3546 | 0.3542 | 18.149 |
| 2.5331 | 6.0 | 7500 | 2.1339 | 0.4189 | 0.2237 | 0.356 | 0.3558 | 18.191 |
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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Model tree for zbigi/bart-base-summarization-medical-51
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facebook/bart-base