---
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