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---
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
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