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---
license: apache-2.0
base_model: sshleifer/distilbart-cnn-6-6
tags:
- generated_from_trainer
datasets:
- wcep-10
metrics:
- rouge
model-index:
- name: thesis-bart-finetuned-on-original-wcep
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: wcep-10
type: wcep-10
config: roberta
split: validation
args: roberta
metrics:
- name: Rouge1
type: rouge
value: 37.2224
---
<!-- 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. -->
# thesis-bart-finetuned-on-original-wcep
This model is a fine-tuned version of [sshleifer/distilbart-cnn-6-6](https://huggingface.co/sshleifer/distilbart-cnn-6-6) on the wcep-10 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9981
- Rouge1: 37.2224
- Rouge2: 16.5575
- Rougel: 26.7904
- Rougelsum: 30.3497
- Gen Len: 67.5627
## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 2.0801 | 1.0 | 510 | 2.0119 | 36.4915 | 16.0165 | 26.3565 | 29.7397 | 67.9882 |
| 1.7597 | 2.0 | 1020 | 1.9868 | 36.9513 | 16.3776 | 26.4974 | 30.1234 | 68.3961 |
| 1.5997 | 3.0 | 1530 | 1.9981 | 37.2224 | 16.5575 | 26.7904 | 30.3497 | 67.5627 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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