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AdaDecode-CodeLlama-13B-Instruct-XSum – AI Model by meng-lab | AlphaNeural AI
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AdaDecode-CodeLlama-13B-Instruct-XSum
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safetensors
alignment-handbook
generated_from_trainer
meng-lab/CodeLlama-13B-Instruct-xsum
meta-llama/CodeLlama-13b-Instruct-hf
finetune
llama2
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CodeLlama-13b-Instruct-sft-5e-3-epoch-100-xsum
This model is a fine-tuned version of
meta-llama/CodeLlama-13b-Instruct-hf
on the meng-lab/CodeLlama-13B-Instruct-xsum dataset.
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: 0.005
train_batch_size: 1
eval_batch_size: 2
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 16
total_train_batch_size: 128
total_eval_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 100
Training results
Framework versions
Transformers 4.43.2
Pytorch 2.1.2
Datasets 3.0.1
Tokenizers 0.19.1
