metadata
base_model: facebook/bart-large
library_name: peft
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: bart-large-summarization-medical_on_cnn-43
results: []
bart-large-summarization-medical_on_cnn-43
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: 3.0298
- Rouge1: 0.2443
- Rouge2: 0.0871
- Rougel: 0.193
- Rougelsum: 0.2171
- Gen Len: 18.859
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: 43
- 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 |
---|---|---|---|---|---|---|---|---|
2.2146 | 1.0 | 1250 | 3.0347 | 0.2365 | 0.083 | 0.1868 | 0.2101 | 19.329 |
2.1322 | 2.0 | 2500 | 3.0354 | 0.2419 | 0.0862 | 0.1911 | 0.2142 | 19.0 |
2.0892 | 3.0 | 3750 | 3.0422 | 0.2411 | 0.0851 | 0.1903 | 0.2134 | 18.943 |
2.0772 | 4.0 | 5000 | 3.0387 | 0.2423 | 0.0857 | 0.1911 | 0.2145 | 18.869 |
2.0742 | 5.0 | 6250 | 3.0307 | 0.2448 | 0.0868 | 0.193 | 0.2171 | 18.828 |
2.0673 | 6.0 | 7500 | 3.0298 | 0.2443 | 0.0871 | 0.193 | 0.2171 | 18.859 |
Framework versions
- PEFT 0.11.1
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1