ale-bay_-_zephyr-2b-gemma-dpo-4bits – AI Model by RichardErkhov | AlphaNeural AI

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ale-bay_-_zephyr-2b-gemma-dpo-4bits

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zephyr-2b-gemma-dpo - bnb 4bits

Model creator: https://huggingface.co/ale-bay/
Original model: https://huggingface.co/ale-bay/zephyr-2b-gemma-dpo/

Original model description:

license: gemma base_model: google/gemma-2b tags:

alignment-handbook
trl
dpo
generated_from_trainer
trl
dpo
generated_from_trainer datasets:
argilla/dpo-mix-7k model-index:
name: zephyr-2b-gemma-dpo results: []

Visualize in Weights & Biases

zephyr-2b-gemma-dpo

This model is a fine-tuned version of google/gemma-2b on the argilla/dpo-mix-7k dataset. It achieves the following results on the evaluation set:

Loss: 0.6493
Rewards/chosen: -0.0415
Rewards/rejected: -0.1402
Rewards/accuracies: 0.6875
Rewards/margins: 0.0986
Logps/rejected: -378.6258
Logps/chosen: -386.1853
Logits/rejected: -25.9826
Logits/chosen: -26.9604

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: 5e-07
train_batch_size: 2
eval_batch_size: 4
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 8
total_train_batch_size: 128
total_eval_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
0.6264	1.8957	100	0.6497	-0.0395	-0.1328	0.6354	0.0933	-378.4776	-386.1444	-25.9802	-26.9529

Framework versions

Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1