---
library_name: transformers
license: other
base_model: sathiiiii/polyalign-qwen2.5-3b-en-sft
tags:
- llama-factory
- full
- generated_from_trainer
- dpo
- trl
model-index:
- name: polyalign
  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. -->

# polyalign

This model is a fine-tuned version of [sathiiiii/polyalign-qwen2.5-3b-en-sft](https://huggingface.co/sathiiiii/polyalign-qwen2.5-3b-en-sft) on the polyalign_dpo_train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3380
- Rewards/chosen: -1.0773
- Rewards/rejected: -4.7114
- Rewards/accuracies: 0.8866
- Rewards/margins: 3.6341
- Logps/chosen: -102.4047
- Logps/rejected: -83.3126
- Logits/chosen: -2.2493
- Logits/rejected: -2.2458

## 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-07
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Logits/chosen | Logits/rejected |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:-------------:|:---------------:|
| 0.2949        | 0.4307 | 3000 | 0.3603          | -1.1292        | -4.2747          | 0.8788             | 3.1456          | -102.9238    | -78.9461       | -2.2672       | -2.2695         |
| 0.2779        | 0.8615 | 6000 | 0.3380          | -1.0773        | -4.7114          | 0.8866             | 3.6341          | -102.4047    | -83.3126       | -2.2493       | -2.2458         |


### Framework versions

- Transformers 4.56.2
- Pytorch 2.9.1+rocm6.3
- Datasets 4.0.0
- Tokenizers 0.22.2