metadata

library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
  - alignment-handbook
  - trl
  - cpo
  - generated_from_trainer
  - trl
  - cpo
  - generated_from_trainer
datasets:
  - princeton-nlp/llama3-ultrafeedback
model-index:
  - name: llama3.1-cpo-full-0912
    results: []

llama3.1-cpo-full-0912

This model is a fine-tuned version of meta-llama/Meta-Llama-3.1-8B-Instruct on the princeton-nlp/llama3-ultrafeedback dataset. It achieves the following results on the evaluation set:

Loss: 1.5985
Rewards/chosen: -15.4365
Rewards/rejected: -16.1367
Rewards/accuracies: 0.6239
Rewards/margins: 0.7002
Logps/rejected: -161.3668
Logps/chosen: -154.3647
Logits/rejected: -0.3853
Logits/chosen: -0.4112
Nll Loss: 0.4210

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-06
train_batch_size: 4
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 8
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: linear
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	Nll Loss
1.9362	0.2311	100	1.7930	-14.9339	-15.2848	0.5761	0.3508	-152.8475	-149.3394	-0.4123	-0.4378	0.4067
1.7019	0.4623	200	1.6786	-15.4303	-16.0131	0.6087	0.5828	-160.1311	-154.3027	-0.3358	-0.3580	0.4193
1.6388	0.6934	300	1.6233	-15.5465	-16.2127	0.6130	0.6662	-162.1269	-155.4650	-0.3582	-0.3828	0.4230
1.632	0.9246	400	1.6007	-15.6505	-16.3448	0.6370	0.6943	-163.4479	-156.5048	-0.3811	-0.4072	0.4277

Framework versions

Transformers 4.44.2
Pytorch 2.3.1
Datasets 2.21.0
Tokenizers 0.19.1