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bart-base-finetuned-samsum
Vailla-Rohit/bart-base-finetuned-samsum
bart-base-finetuned-samsum is a machine learning model from Vailla-Rohit. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- Library
- transformers
- License
- apache-2.0
- Model type
- bart
- Access
- Public
- Created
- May 9, 2023
- Updated
- May 9, 2023
- SHA
- df5fd8ce
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. -->
test-dialogue-summarization
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: 1.5507
- Rouge1: 48.0348
- Rouge2: 24.8215
- Rougel: 40.5048
- Rougelsum: 44.3467
- Gen Len: 18.1638
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: 9e-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 460 | 1.5507 | 48.0348 | 24.8215 | 40.5048 | 44.3467 | 18.1638 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- May 9, 2023
- Updated
- May 9, 2023