---
license: mit
base_model: facebook/bart-large-cnn
tags:
- generated_from_trainer
datasets:
- xsum
metrics:
- rouge
model-index:
- name: theus_concepttagger
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: xsum
      type: xsum
      config: default
      split: validation
      args: default
    metrics:
    - name: Rouge1
      type: rouge
      value: 34.8663
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# theus_concepttagger

This model is a fine-tuned version of [facebook/bart-large-cnn](https://huggingface.co/facebook/bart-large-cnn) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6249
- Rouge1: 34.8663
- Rouge2: 15.1526
- Rougel: 26.1224
- Rougelsum: 26.5164
- Gen Len: 62.4475

## 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: 1

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.4096        | 1.0   | 12753 | 1.6249          | 34.8663 | 15.1526 | 26.1224 | 26.5164   | 62.4475 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3