bart-large-summarization-medical_on_cnn-42
This model is a fine-tuned version of facebook/bart-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.0346
- Rouge1: 0.2419
- Rouge2: 0.0864
- Rougel: 0.1915
- Rougelsum: 0.2157
- Gen Len: 18.758
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: 42
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.2338 | 1.0 | 1250 | 3.0353 | 0.238 | 0.084 | 0.1872 | 0.211 | 19.412 |
| 2.1329 | 2.0 | 2500 | 3.0331 | 0.2383 | 0.0835 | 0.1873 | 0.2116 | 19.091 |
| 2.0982 | 3.0 | 3750 | 3.0363 | 0.2412 | 0.0861 | 0.1911 | 0.2148 | 18.84 |
| 2.0827 | 4.0 | 5000 | 3.0470 | 0.2412 | 0.0865 | 0.191 | 0.2146 | 18.745 |
| 2.0732 | 5.0 | 6250 | 3.0370 | 0.2421 | 0.0865 | 0.1915 | 0.2157 | 18.798 |
| 2.0714 | 6.0 | 7500 | 3.0346 | 0.2419 | 0.0864 | 0.1915 | 0.2157 | 18.758 |
Framework versions
- PEFT 0.11.1
- 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-large-summarization-medical_on_cnn-42
Base model
facebook/bart-large