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bart-fine-tuned-on-summarization
ashishbaraiya/bart-fine-tuned-on-summarization
bart-fine-tuned-on-summarization is a machine learning model from ashishbaraiya. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- bart
- Access
- Public
- Created
- Mar 12, 2024
- Updated
- Mar 12, 2024
- SHA
- adf04045
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-fine-tuned-on-summarization
This model is a fine-tuned version of ccdv/lsg-bart-base-16384-mediasum on the pubmed-summarization dataset. It achieves the following results on the evaluation set:
- Loss: 2.7293
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: 5e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.4477 | 0.2 | 100 | 3.1109 |
| 3.0893 | 0.4 | 200 | 2.8719 |
| 2.8441 | 0.6 | 300 | 2.7832 |
| 2.9203 | 0.8 | 400 | 2.7402 |
| 2.9796 | 1.0 | 500 | 2.7293 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Library
- transformers
- Type
- bart
- Created
- Mar 12, 2024
- Updated
- Mar 12, 2024