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BART_large_Synthetic_Gameplan
Koshti10/BART_large_Synthetic_Gameplan
BART_large_Synthetic_Gameplan is a machine learning model from Koshti10. 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
- Sep 23, 2023
- Updated
- Sep 23, 2023
- SHA
- a56d022a
Base models
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_large_Synthetic_Gameplan
This model is a fine-tuned version of Koshti10/BART-large-ET-Synthetic on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.2557
- Rouge1: 38.2255
- Rouge2: 27.7473
- Rougel: 35.4392
- Rougelsum: 35.414
- Gen Len: 19.2554
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 20
- label_smoothing_factor: 0.1
Training results
Framework versions
- Transformers 4.33.2
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Library
- transformers
- Type
- bart
- License
- apache-2.0
- Created
- Sep 23, 2023
- Updated
- Sep 23, 2023