---
base_model: deepseek-ai/deepseek-coder-1.3b-base
tags:
- trl
- kto
- generated_from_trainer
model-index:
- name: k2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/stojchets/huggingface/runs/k2)
# k2

This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1672
- Eval/rewards/chosen: 2.6052
- Eval/logps/chosen: -116.5449
- Eval/rewards/rejected: -11.1897
- Eval/logps/rejected: -292.9474
- Eval/rewards/margins: 13.7949
- Eval/kl: 8.4275

## 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: 5e-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: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |        |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.1178        | 1.7058 | 100  | 0.1672          | 8.4275 |


### Framework versions

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