Visualize in Weights & Biases

dpo5k2

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: 6.1354
  • Rewards/chosen: -37.3199
  • Rewards/rejected: -114.4451
  • Rewards/accuracies: 0.7599
  • Rewards/margins: 77.1251
  • Logps/rejected: -1316.1266
  • Logps/chosen: -541.0429
  • Logits/rejected: -13.2895
  • Logits/chosen: -11.3220

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: 0.001
  • 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: 3

Training results

Training Loss Epoch Step Validation Loss Rewards/chosen Rewards/rejected Rewards/accuracies Rewards/margins Logps/rejected Logps/chosen Logits/rejected Logits/chosen
0.147 2.5744 100 6.1354 -37.3199 -114.4451 0.7599 77.1251 -1316.1266 -541.0429 -13.2895 -11.3220

Framework versions

  • Transformers 4.43.0.dev0
  • Pytorch 2.2.2+cu121
  • Datasets 2.19.2
  • Tokenizers 0.19.1
Downloads last month
23
Safetensors
Model size
1.35B params
Tensor type
F32
·
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for stojchet/dpo5k2

Finetuned
(100)
this model
Finetunes
1 model