This model is a fine-tuned version of deepseek-ai/deepseek-coder-1.3b-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.5000
Eval/rewards/chosen: -1067.9947
Eval/logps/chosen: -10717.3285
Eval/rewards/rejected: -1034.4163
Eval/logps/rejected: -10418.6161
Eval/rewards/margins: -33.5784
Eval/kl: 0.0

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: 0.15
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_ratio: 0.1
lr_scheduler_warmup_steps: 200
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.5004	1.1552	100	0.5000
0.502	2.3105	200	0.5000
0.4995	3.4657	300	0.5000

Framework versions

Transformers 4.45.0
Pytorch 2.5.1+cu124
Datasets 2.19.2
Tokenizers 0.20.3

stojchet/kto3

kto3

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

stojchet/
kto3