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TTTXXX01/
LLama-8B-Instruct-v0.1-MI-2e-5

Name: LLama-8B-Instruct-v0.1-MI-2e-5
Availability: InStock

safetensors

llama

alignment_handbook-handbook

generated_from_trainer

princeton-nlp/llama3-ultrafeedback

meta-llama/Meta-Llama-3-8B-Instruct

finetune

llama3

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LLama-8B-Instruct-v0.1-MI-2e-5

This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on the princeton-nlp/llama3-ultrafeedback dataset. It achieves the following results on the evaluation set:

Loss: 1.2552
Rewards/chosen: -0.5792
Rewards/rejected: -0.7270
Rewards/accuracies: 0.6626
Rewards/margins: 0.1478
Logps/rejected: -0.7270
Logps/chosen: -0.5792
Logits/rejected: -0.3939
Logits/chosen: -0.3830

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: 2e-05
train_batch_size: 2
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 4
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: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
1.2571	0.8550	400	1.2552	-0.5792	-0.7270	0.6626	0.1478	-0.7270	-0.5792	-0.3939	-0.3830

Framework versions

Transformers 4.42.0
Pytorch 2.1.2+cu121
Datasets 2.14.6
Tokenizers 0.19.1

TTTXXX01/LLama-8B-Instruct-v0.1-MI-2e-5

LLama-8B-Instruct-v0.1-MI-2e-5

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

TTTXXX01/
LLama-8B-Instruct-v0.1-MI-2e-5