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bart-base-finetuned-samsum-en
santiviquez/bart-base-finetuned-samsum-en
bart-base-finetuned-samsum-en is a summarization model from santiviquez. Use it when you need a shorter version of a longer text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Summarization
- Library
- transformers
- License
- apache-2.0
- Model type
- bart
- Access
- Public
- Created
- Jun 3, 2022
- Updated
- Dec 20, 2023
- SHA
- 5b4e8851
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Base models
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
bart-base-finetuned-samsum-en
This model is a fine-tuned version of facebook/bart-base on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.3676
- Rouge1: 46.8825
- Rouge2: 22.0923
- Rougel: 39.7249
- Rougelsum: 42.9187
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: 5.6e-05
- train_batch_size: 10
- eval_batch_size: 10
- 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 | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 0.5172 | 1.0 | 300 | 2.1613 | 47.4152 | 22.8106 | 39.93 | 43.3639 |
| 0.3627 | 2.0 | 600 | 2.2771 | 47.2676 | 22.6325 | 40.1345 | 43.19 |
| 0.2466 | 3.0 | 900 | 2.3676 | 46.8825 | 22.0923 | 39.7249 | 42.9187 |
Framework versions
- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
- Task
- Summarization
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- Jun 3, 2022
- Updated
- Dec 20, 2023