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README.md
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model-index:
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- name: rag-tge_Llama-3-8B_LoRA
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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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# rag-tge_Llama-3-8B_LoRA
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on an unknown dataset.
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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: 0.0002
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- train_batch_size: 1
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- eval_batch_size: 1
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- seed: 50
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- gradient_accumulation_steps: 8
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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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- lr_scheduler_warmup_ratio: 0.03
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- num_epochs: 3
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### Framework versions
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- PEFT 0.10.0
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- Transformers 4.40.2
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- Pytorch 2.3.0+cu121
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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model-index:
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- name: rag-tge_Llama-3-8B_LoRA
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results: []
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datasets:
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- tdolega/rag-tge_finetuning-dataset
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language:
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- en
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---
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[Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) finetuned on [rag-tge_finetuning-dataset](https://huggingface.co/datasets/tdolega/rag-tge_finetuning-dataset).for [rag-tge](https://github.com/tdolega/rag-tge) project.
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