Mitsuki-Sakamoto
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fdpo-models

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SFT Model 160m

This model is a fine-tuned version of EleutherAI/pythia-160m on an alpaca_farm dataset.

The following hyperparameters were used during training:

learning_rate: 8e-06
train_batch_size: 4
seed: 1
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
num_epochs: 3

SFT Model 1.4b

This model is a fine-tuned version of EleutherAI/pythia-1.4b on the alpaca_farm dataset.

The following hyperparameters were used during training:

learning_rate: 8e-06
train_batch_size: 4
seed: 1
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
num_epochs: 3

Reward Model 70m

This model is a fine-tuned version of EleutherAI/pythia-70m on the fdpo-preference-dataset dataset.

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 16
seed: [1, 2, 3]
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
num_epochs: 2

Reward Model 160m

This model is a fine-tuned version of EleutherAI/pythia-160m on the fdpo-preference-dataset dataset.

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 16
seed: [1, 2, 3]
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: constant
num_epochs: 2

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