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---
library_name: transformers
license: apache-2.0
base_model: niteshsah-760/BART-LARGE-DIALOGSUM
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: BART-LARGE-fine_tuned
  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-LARGE-fine_tuned

This model is a fine-tuned version of [niteshsah-760/BART-LARGE-DIALOGSUM](https://huggingface.co/niteshsah-760/BART-LARGE-DIALOGSUM) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5467
- Rouge1: 58.168
- Rouge2: 45.9825
- Rougel: 54.3562
- Rougelsum: 54.4552

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use 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: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|
| 0.6587        | 1.0   | 563  | 0.6037          | 56.3206 | 44.2624 | 52.832  | 52.8704   |
| 0.6162        | 2.0   | 1126 | 0.5719          | 56.8789 | 44.8139 | 53.3803 | 53.4437   |
| 0.5815        | 3.0   | 1689 | 0.5560          | 57.6576 | 45.5559 | 53.943  | 54.0187   |
| 0.5663        | 4.0   | 2252 | 0.5491          | 57.9815 | 45.9701 | 54.2183 | 54.3077   |
| 0.546         | 5.0   | 2815 | 0.5467          | 58.168  | 45.9825 | 54.3562 | 54.4552   |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0