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---
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library_name: transformers
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license: apache-2.0
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base_model: facebook/bart-base
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tags:
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- generated_from_trainer
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metrics:
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- rouge
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model-index:
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- name: LLM_Project_Lighthouse
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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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# LLM_Project_Lighthouse
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on
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It achieves the following results on the evaluation set:
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- Loss: 3.1391
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- Rouge1: 0.4048
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- Rouge2: 0.1271
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- Rougel: 0.3715
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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: 3e-05
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- train_batch_size: 4
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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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: 4
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- mixed_precision_training: Native AMP
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### Training results
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu118
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- Datasets 3.0.0
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- Tokenizers 0.19.1
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---
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library_name: transformers
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license: apache-2.0
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base_model: facebook/bart-base
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+
tags:
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- generated_from_trainer
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metrics:
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- rouge
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model-index:
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- name: LLM_Project_Lighthouse
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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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+
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# LLM_Project_Lighthouse
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This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on the multi_news dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.1391
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+
- Rouge1: 0.4048
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+
- Rouge2: 0.1271
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- Rougel: 0.3715
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+
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## Model description
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+
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More information needed
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+
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## Intended uses & limitations
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+
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+
More information needed
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+
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+
## Training and evaluation data
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+
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+
More information needed
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+
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+
## Training procedure
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+
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### Training hyperparameters
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+
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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+
- train_batch_size: 4
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+
- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 8
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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: 4
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- mixed_precision_training: Native AMP
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+
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### Training results
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+
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### Framework versions
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- Transformers 4.44.2
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- Pytorch 2.4.1+cu118
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- Datasets 3.0.0
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- Tokenizers 0.19.1
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