|
|
--- |
|
|
license: apache-2.0 |
|
|
base_model: facebook/bart-base |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: bart-base-pubmed-1024 |
|
|
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-pubmed-1024 |
|
|
|
|
|
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: 4.2410 |
|
|
- Rouge1: 43.6037 |
|
|
- Rouge2: 17.2895 |
|
|
- Rougel: 25.6916 |
|
|
- Rougelsum: 38.819 |
|
|
- Gen Len: 207.62 |
|
|
|
|
|
## 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: 0.0008 |
|
|
- train_batch_size: 16 |
|
|
- eval_batch_size: 4 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 4 |
|
|
- total_train_batch_size: 64 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: polynomial |
|
|
- lr_scheduler_warmup_steps: 500 |
|
|
- num_epochs: 4 |
|
|
- mixed_precision_training: Native AMP |
|
|
- label_smoothing_factor: 0.2 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:| |
|
|
| 4.8142 | 0.27 | 500 | 4.7781 | 37.4249 | 13.3533 | 21.8304 | 33.5429 | 167.98 | |
|
|
| 4.7227 | 0.55 | 1000 | 4.6067 | 40.4166 | 14.7121 | 23.5203 | 36.1746 | 187.26 | |
|
|
| 4.6406 | 0.82 | 1500 | 4.5968 | 40.7033 | 15.1399 | 23.7701 | 36.3048 | 187.96 | |
|
|
| 4.5179 | 1.09 | 2000 | 4.4875 | 41.2297 | 15.7839 | 23.797 | 36.6246 | 189.1 | |
|
|
| 4.5044 | 1.36 | 2500 | 4.4398 | 41.7532 | 15.7797 | 24.5182 | 37.5172 | 203.19 | |
|
|
| 4.4599 | 1.64 | 3000 | 4.4042 | 42.9839 | 16.5654 | 25.0308 | 38.1967 | 210.62 | |
|
|
| 4.4092 | 1.91 | 3500 | 4.3640 | 42.2944 | 16.3717 | 24.6831 | 37.5064 | 211.33 | |
|
|
| 4.3226 | 2.18 | 4000 | 4.3496 | 42.6501 | 16.4452 | 24.7418 | 38.2741 | 225.19 | |
|
|
| 4.3078 | 2.46 | 4500 | 4.3160 | 42.7482 | 16.9222 | 25.4787 | 38.5397 | 207.54 | |
|
|
| 4.2834 | 2.73 | 5000 | 4.2992 | 42.6235 | 16.9886 | 25.3069 | 38.5346 | 205.73 | |
|
|
| 4.2535 | 3.0 | 5500 | 4.2865 | 42.8731 | 16.8583 | 25.6184 | 38.498 | 203.19 | |
|
|
| 4.1865 | 3.28 | 6000 | 4.2658 | 43.2303 | 17.154 | 25.7881 | 38.7525 | 215.33 | |
|
|
| 4.165 | 3.55 | 6500 | 4.2536 | 44.1507 | 17.211 | 26.02 | 39.5668 | 206.67 | |
|
|
| 4.155 | 3.82 | 7000 | 4.2410 | 43.6037 | 17.2895 | 25.6916 | 38.819 | 207.62 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.37.2 |
|
|
- Pytorch 2.0.1+cu117 |
|
|
- Datasets 2.14.4 |
|
|
- Tokenizers 0.15.2 |
|
|
|
