This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: nan
Rewards/chosen: nan
Rewards/rejected: nan
Rewards/accuracies: 0.6747
Rewards/margins: nan
Logps/rejected: nan
Logps/chosen: nan
Logits/rejected: nan
Logits/chosen: nan

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: 0.05
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 200
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rewards/chosen	Rewards/rejected	Rewards/accuracies	Rewards/margins	Logps/rejected	Logps/chosen	Logits/rejected	Logits/chosen
1059.7216	2.3088	100	nan	nan	nan	0.6747	nan	nan	nan	nan	nan

Framework versions

Transformers 4.45.0
Pytorch 2.5.1+cu124
Datasets 2.19.2
Tokenizers 0.20.3

stojchet/dpo6

dpo6

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

stojchet/
dpo6