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

Loss: 0.0465
Rewards/chosen: 1.3306
Rewards/rejected: -5.9771
Rewards/accuracies: 0.9934
Rewards/margins: 7.3077
Logps/rejected: -232.7393
Logps/chosen: -155.1493
Logits/rejected: -16.8463
Logits/chosen: -16.6346

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-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 64
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: 2
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
0.1691	1.7149	100	0.0465	1.3306	-5.9771	0.9934	7.3077	-232.7393	-155.1493	-16.8463	-16.6346

Framework versions

Transformers 4.43.0.dev0
Pytorch 2.2.2+cu121
Datasets 2.19.2
Tokenizers 0.19.1

RichardErkhov/stojchet_-_ndpo1-awq

Original model description:

ndpo1

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
stojchet_-_ndpo1-awq