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---
license: mit
base_model: facebook/bart-base
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: train-bart-base
results: []
datasets:
- knkarthick/dialogsum
language:
- en
pipeline_tag: summarization
---
<!-- 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. -->
# train-bart-base
This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on [knkarthick/dialogsum](https://huggingface.co/datasets/knkarthick/dialogsum) dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2710
- Rouge1: 42.8665
- Rouge2: 21.8559
- Rougel: 37.536
- Rougelsum: 39.3725
- Gen Len: 18.0
## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 0.3316 | 1.0 | 1557 | 0.2421 | 41.223 | 19.5022 | 35.5882 | 38.1294 | 18.0 |
| 0.2448 | 2.0 | 3115 | 0.2304 | 41.9635 | 20.5356 | 36.729 | 38.7748 | 18.0 |
| 0.2088 | 3.0 | 4672 | 0.2317 | 41.1639 | 20.168 | 35.9644 | 38.0607 | 18.0 |
| 0.1811 | 4.0 | 6230 | 0.2352 | 42.5001 | 21.4806 | 37.0514 | 39.0242 | 18.0 |
| 0.1591 | 5.0 | 7787 | 0.2422 | 42.148 | 20.9001 | 36.7976 | 38.6102 | 18.0 |
| 0.1399 | 6.0 | 9345 | 0.2465 | 42.1862 | 21.1403 | 36.7742 | 38.7401 | 18.0 |
| 0.1247 | 7.0 | 10902 | 0.2535 | 42.8571 | 21.998 | 37.6668 | 39.5963 | 18.0 |
| 0.1115 | 8.0 | 12460 | 0.2609 | 42.2841 | 21.1273 | 36.9562 | 38.9423 | 18.0 |
| 0.1019 | 9.0 | 14017 | 0.2677 | 42.8866 | 21.6628 | 37.5422 | 39.4627 | 18.0 |
| 0.0946 | 10.0 | 15570 | 0.2710 | 42.8665 | 21.8559 | 37.536 | 39.3725 | 18.0 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.19.1
- Tokenizers 0.15.2 |