transformers pytorch tensorboard bart text2text-generation summarization generated_from_trainer dataset:cnn_dailymail license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
datasets:
- cnn_dailymail
license: apache-2.0
tags:
- summarization
- generated_from_trainer
model-index:
- name: bart-base-finetuned-summarization-cnn-ver1.3
  results: []
---

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# bart-base-finetuned-summarization-cnn-ver1.3

This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the cnn_dailymail dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3148
- Bertscore-mean-precision: 0.8890
- Bertscore-mean-recall: 0.8603
- Bertscore-mean-f1: 0.8742
- Bertscore-median-precision: 0.8874
- Bertscore-median-recall: 0.8597
- Bertscore-median-f1: 0.8726

## 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: 4e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bertscore-mean-precision | Bertscore-mean-recall | Bertscore-mean-f1 | Bertscore-median-precision | Bertscore-median-recall | Bertscore-median-f1 |
|:-------------:|:-----:|:-----:|:---------------:|:------------------------:|:---------------------:|:-----------------:|:--------------------------:|:-----------------------:|:-------------------:|
| 2.3735        | 1.0   | 5742  | 2.2581          | 0.8831                   | 0.8586                | 0.8705            | 0.8834                     | 0.8573                  | 0.8704              |
| 1.744         | 2.0   | 11484 | 2.2479          | 0.8920                   | 0.8620                | 0.8765            | 0.8908                     | 0.8603                  | 0.8752              |
| 1.3643        | 3.0   | 17226 | 2.3148          | 0.8890                   | 0.8603                | 0.8742            | 0.8874                     | 0.8597                  | 0.8726              |


### Framework versions

- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
