metadata
base_model: facebook/bart-base
library_name: peft
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: bart-base-summarization-medical_on_cnn-49
results: []
bart-base-summarization-medical_on_cnn-49
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: 3.3782
- Rouge1: 0.2538
- Rouge2: 0.0951
- Rougel: 0.1997
- Rougelsum: 0.2242
- Gen Len: 18.562
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: 49
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.699 | 1.0 | 1250 | 3.3753 | 0.2516 | 0.0907 | 0.1966 | 0.2214 | 19.026 |
| 2.6011 | 2.0 | 2500 | 3.3638 | 0.2505 | 0.0913 | 0.1968 | 0.2211 | 18.839 |
| 2.578 | 3.0 | 3750 | 3.3738 | 0.2516 | 0.0918 | 0.1971 | 0.2208 | 18.888 |
| 2.532 | 4.0 | 5000 | 3.3729 | 0.2523 | 0.0946 | 0.1993 | 0.223 | 18.506 |
| 2.5583 | 5.0 | 6250 | 3.3794 | 0.2528 | 0.0939 | 0.1984 | 0.2233 | 18.612 |
| 2.539 | 6.0 | 7500 | 3.3782 | 0.2538 | 0.0951 | 0.1997 | 0.2242 | 18.562 |
Framework versions
- PEFT 0.12.0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1