---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: bert-small2bert-small-finetuned-cnn_daily_mail-summarization-newsroom-filtered
  results: []
---

<!-- 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. -->

# bert-small2bert-small-finetuned-cnn_daily_mail-summarization-newsroom-filtered

This model is a fine-tuned version of [mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization](https://huggingface.co/mrm8488/bert-small2bert-small-finetuned-cnn_daily_mail-summarization) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5413
- Rouge1: 32.3232
- Rouge2: 20.9203
- Rougel: 27.232
- Rougelsum: 29.345
- Gen Len: 72.2217

## 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
- lr_scheduler_warmup_steps: 500
- num_epochs: 5
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 3.796         | 0.89  | 405  | 3.6945          | 29.7168 | 17.6705 | 24.4204 | 26.484    | 69.6847 |
| 3.6426        | 1.78  | 810  | 3.5532          | 32.3051 | 20.8789 | 27.1724 | 29.384    | 72.3695 |
| 3.2645        | 2.66  | 1215 | 3.5437          | 32.2016 | 20.758  | 27.083  | 29.0954   | 73.3892 |
| 3.1719        | 3.55  | 1620 | 3.5377          | 32.5493 | 21.083  | 27.0881 | 29.4691   | 71.5222 |
| 2.9763        | 4.44  | 2025 | 3.5413          | 32.3232 | 20.9203 | 27.232  | 29.345    | 72.2217 |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1