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llama3.1-8b-instruct-int4-edgar-summarization

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llama3.1-8b-instruct-int4-edgar-summarization

This model is a fine-tuned version of hugging-quants/Meta-Llama-3.1-8B-Instruct-GPTQ-INT4 on the generator dataset.

Model description

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Intended uses & limitations

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Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0002
train_batch_size: 1
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 12
total_train_batch_size: 12
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
lr_scheduler_warmup_ratio: 0.03
num_epochs: 3

Training results

Framework versions

PEFT 0.12.0
Transformers 4.43.4
Pytorch 2.4.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1

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Model tree for liamjdavis/llama3.1-8b-instruct-int4-edgar-summarization

Base model

hugging-quants/Meta-Llama-3.1-8B-Instruct-GPTQ-INT4

Adapter

(2)

this model

Evaluation results

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