|
--- |
|
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-47 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# bart-base-summarization-medical_on_cnn-47 |
|
|
|
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 3.3826 |
|
- Rouge1: 0.2498 |
|
- Rouge2: 0.0937 |
|
- Rougel: 0.1992 |
|
- Rougelsum: 0.2218 |
|
- Gen Len: 18.217 |
|
|
|
## 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: 47 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:| |
|
| 2.7195 | 1.0 | 1250 | 3.3721 | 0.2478 | 0.0885 | 0.1948 | 0.219 | 18.949 | |
|
| 2.6054 | 2.0 | 2500 | 3.3830 | 0.251 | 0.0932 | 0.1977 | 0.2222 | 18.61 | |
|
| 2.572 | 3.0 | 3750 | 3.3801 | 0.251 | 0.092 | 0.1978 | 0.2222 | 18.472 | |
|
| 2.5529 | 4.0 | 5000 | 3.3811 | 0.2495 | 0.0927 | 0.1992 | 0.2215 | 18.222 | |
|
| 2.5453 | 5.0 | 6250 | 3.3833 | 0.2496 | 0.0918 | 0.1983 | 0.2219 | 18.318 | |
|
| 2.5151 | 6.0 | 7500 | 3.3826 | 0.2498 | 0.0937 | 0.1992 | 0.2218 | 18.217 | |
|
|
|
|
|
### Framework versions |
|
|
|
- PEFT 0.12.0 |
|
- Transformers 4.42.4 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
