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: 0.5
Eval/rewards/chosen: -448.8974
Eval/logps/chosen: -4526.3562
Eval/rewards/rejected: -433.3957
Eval/logps/rejected: -4408.4109
Eval/rewards/margins: -15.5017
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: 0.05
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_ratio: 0.1
lr_scheduler_warmup_steps: 200
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
0.5029	1.1552	100	0.5028
0.502	2.3105	200	0.5000
0.4998	3.4657	300	0.5000
0.5002	4.6209	400	0.5000
0.501	5.7762	500	0.5000
0.4994	6.9314	600	0.5000
0.4998	8.0866	700	0.5000
0.501	9.2419	800	0.5

Framework versions

Transformers 4.45.0
Pytorch 2.5.1+cu124
Datasets 2.19.2
Tokenizers 0.20.3

stojchet/kto6

kto6

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

stojchet/
kto6