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README.md
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---
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license: apache-2.0
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tags:
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- summarization
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- generated_from_trainer
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datasets:
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- cnn_dailymail
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model-index:
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- name: bart-base-finetuned-summarization-cnn-ver1.3
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# bart-base-finetuned-summarization-cnn-ver1.3
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the cnn_dailymail dataset.
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It achieves the following results on the evaluation set:
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- Loss: 2.3148
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- Bertscore-mean-precision: 0.8890
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- Bertscore-mean-recall: 0.8603
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- Bertscore-mean-f1: 0.8742
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- Bertscore-median-precision: 0.8874
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- Bertscore-median-recall: 0.8597
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- Bertscore-median-f1: 0.8726
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 4e-05
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Bertscore-mean-precision | Bertscore-mean-recall | Bertscore-mean-f1 | Bertscore-median-precision | Bertscore-median-recall | Bertscore-median-f1 |
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|:-------------:|:-----:|:-----:|:---------------:|:------------------------:|:---------------------:|:-----------------:|:--------------------------:|:-----------------------:|:-------------------:|
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| 2.3735 | 1.0 | 5742 | 2.2581 | 0.8831 | 0.8586 | 0.8705 | 0.8834 | 0.8573 | 0.8704 |
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| 1.744 | 2.0 | 11484 | 2.2479 | 0.8920 | 0.8620 | 0.8765 | 0.8908 | 0.8603 | 0.8752 |
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| 1.3643 | 3.0 | 17226 | 2.3148 | 0.8890 | 0.8603 | 0.8742 | 0.8874 | 0.8597 | 0.8726 |
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### Framework versions
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- Transformers 4.24.0
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- Pytorch 1.12.1+cu113
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- Datasets 2.7.1
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- Tokenizers 0.13.2
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