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LLama3-8B-Ins-SFT-WebRL-LoRA – AI Model by TiramisuQiao | AlphaNeural AI
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TiramisuQiao
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LLama3-8B-Ins-SFT-WebRL-LoRA
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peft
tensorboard
safetensors
llama-factory
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meta-llama/Meta-Llama-3-8B-Instruct
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TiramisuQiao/LLama3-8B-Ins-SFT-WebRL-LoRA
This model is a fine-tuned version of Meta-Llama-3-8B-Instruct on the web_policy_sft dataset. It achieves the following results on the evaluation set:
Loss: 0.4631
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: 1e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 32
total_eval_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
1.0437
0.1878
50
1.0606
0.5727
0.3756
100
0.5909
0.5279
0.5634
150
0.4970
0.4961
0.7512
200
0.4700
0.4797
0.9390
250
0.4632
Framework versions
PEFT 0.15.2
Transformers 4.53.1
Pytorch 2.3.1+cu121
Datasets 3.2.0
Tokenizers 0.21.1
