led-base-16384-biolaysum-both-umls
This model is a fine-tuned version of allenai/led-base-16384 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.1590
- Rouge1: 0.4539
- Rouge2: 0.1554
- Rougel: 0.2428
- Rougelsum: 0.2427
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: 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: 4
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
---|---|---|---|---|---|---|---|
2.2744 | 0.69 | 5000 | 2.2223 | 0.4492 | 0.1524 | 0.2419 | 0.2418 |
2.0397 | 1.37 | 10000 | 2.1590 | 0.4539 | 0.1554 | 0.2428 | 0.2427 |
1.9233 | 2.06 | 15000 | 2.1238 | 0.4554 | 0.1537 | 0.2417 | 0.2417 |
1.9027 | 2.75 | 20000 | 2.1115 | 0.4556 | 0.1542 | 0.2404 | 0.2404 |
1.78 | 3.43 | 25000 | 2.0991 | 0.4544 | 0.1523 | 0.2411 | 0.2411 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.12.1
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