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---
license: other
base_model: deepseek-ai/deepseek-coder-1.3b-base
tags:
- trl
- dpo
- generated_from_trainer
datasets:
- generator
model-index:
- name: d1
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/d1)
# d1
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 generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1395
- Rewards/chosen: -0.1261
- Rewards/rejected: -19.6585
- Rewards/accuracies: 0.9737
- Rewards/margins: 19.5324
- Logps/rejected: -369.5529
- Logps/chosen: -169.7162
- Logits/rejected: -9.2987
- Logits/chosen: -8.0855
## 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: 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: 4
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0841 | 1.7149 | 100 | 0.0542 | 0.8716 | -12.2566 | 0.9737 | 13.1282 | -295.5336 | -159.7391 | -16.8791 | -17.5293 |
| 0.0013 | 3.4298 | 200 | 0.1395 | -0.1261 | -19.6585 | 0.9737 | 19.5324 | -369.5529 | -169.7162 | -9.2987 | -8.0855 |
### Framework versions
- Transformers 4.43.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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