|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: NazzX1/NoteBART |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- rouge |
|
|
model-index: |
|
|
- name: BART-dialog-sum |
|
|
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-dialog-sum |
|
|
|
|
|
This model is a fine-tuned version of [NazzX1/NoteBART](https://huggingface.co/NazzX1/NoteBART) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.1419 |
|
|
- Rouge1: 0.5285 |
|
|
- Rouge2: 0.3359 |
|
|
- Rougel: 0.4447 |
|
|
|
|
|
## 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: 2e-05 |
|
|
- train_batch_size: 1 |
|
|
- eval_batch_size: 1 |
|
|
- seed: 42 |
|
|
- gradient_accumulation_steps: 2 |
|
|
- total_train_batch_size: 2 |
|
|
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 3 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:| |
|
|
| 0.0732 | 1.0 | 520 | 0.1359 | 0.5626 | 0.3635 | 0.4701 | |
|
|
| 0.0616 | 2.0 | 1040 | 0.1361 | 0.5231 | 0.3261 | 0.4329 | |
|
|
| 0.0411 | 3.0 | 1560 | 0.1419 | 0.5285 | 0.3359 | 0.4447 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.50.3 |
|
|
- Pytorch 2.6.0+cu124 |
|
|
- Datasets 3.5.0 |
|
|
- Tokenizers 0.21.1 |
|
|
|
