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---
license: apache-2.0
base_model: allenai/led-base-16384
tags:
- generated_from_trainer
datasets:
- wcep-10
metrics:
- rouge
model-index:
- name: thesis-led-finetuned-on-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: 43.4358
---
<!-- 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-led-finetuned-on-wcep
This model is a fine-tuned version of [allenai/led-base-16384](https://huggingface.co/allenai/led-base-16384) on the wcep-10 dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6816
- Rouge1: 43.4358
- Rouge2: 21.8159
- Rougel: 35.0411
- Rougelsum: 36.1007
- Gen Len: 27.2843
## 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: 4
- eval_batch_size: 4
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.6843 | 1.0 | 2040 | 1.6753 | 42.8519 | 21.8933 | 35.0226 | 35.9911 | 25.6647 |
| 1.4083 | 2.0 | 4080 | 1.6672 | 43.5166 | 22.0845 | 35.283 | 36.4006 | 26.4098 |
| 1.1981 | 3.0 | 6120 | 1.6816 | 43.4358 | 21.8159 | 35.0411 | 36.1007 | 27.2843 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
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