transformers pytorch tensorboard encoder-decoder text2text-generation generated_from_trainer dataset:xsum license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- xsum
license: apache-2.0
metrics:
- rouge
tags:
- generated_from_trainer
model-index:
- name: bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization-finetuned-xsum
  results:
  - task:
      type: text2text-generation
      name: Sequence-to-sequence Language Modeling
    dataset:
      name: xsum
      type: xsum
      config: default
      split: validation
      args: default
    metrics:
    - type: rouge
      value: 24.9094
      name: Rouge1
---

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# bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization-finetuned-xsum

This model is a fine-tuned version of [mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization](https://huggingface.co/mrm8488/bert-mini2bert-mini-finetuned-cnn_daily_mail-summarization) on the xsum dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9401
- Rouge1: 24.9094
- Rouge2: 7.3754
- Rougel: 18.2282
- Rougelsum: 18.9508
- Gen Len: 61.4478

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:------:|:-------:|:---------:|:-------:|
| 3.0991        | 1.0   | 12753 | 2.9401          | 24.9094 | 7.3754 | 18.2282 | 18.9508   | 61.4478 |


### Framework versions

- Transformers 4.30.0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.13.3
