---
license: apache-2.0
base_model: roofdancer/thesis-bart-finetuned
tags:
- generated_from_trainer
datasets:
- wcep-10
metrics:
- rouge
model-index:
- name: thesis-bart-finetuned-on-original-wcep-500
  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: 35.0169
---

<!-- 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-500

This model is a fine-tuned version of [roofdancer/thesis-bart-finetuned](https://huggingface.co/roofdancer/thesis-bart-finetuned) on the wcep-10 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1217
- Rouge1: 35.0169
- Rouge2: 14.4075
- Rougel: 24.4949
- Rougelsum: 28.2941
- Gen Len: 71.6902

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| No log        | 1.0   | 32   | 2.1140          | 34.7405 | 14.1273 | 24.143  | 28.0926   | 71.6676 |
| No log        | 2.0   | 64   | 2.1159          | 35.1873 | 14.5677 | 24.6163 | 28.2788   | 71.5127 |
| No log        | 3.0   | 96   | 2.1217          | 35.0169 | 14.4075 | 24.4949 | 28.2941   | 71.6902 |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2