---
library_name: transformers
license: other
base_model: trl-lib/qwen1.5-0.5b-sft
tags:
- alignment-handbook
- trl
- simpo
- generated_from_trainer
- trl
- simpo
- generated_from_trainer
datasets:
- yakazimir/ultrafeedback_binarized
model-index:
- name: qwen_cpo_entropy_0_1
  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. -->

# qwen_cpo_entropy_0_1

This model is a fine-tuned version of [trl-lib/qwen1.5-0.5b-sft](https://huggingface.co/trl-lib/qwen1.5-0.5b-sft) on the yakazimir/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7405
- Sft Loss: 1.6848
- Rewards/chosen: -1.7146
- Rewards/rejected: -2.3727
- Rewards/accuracies: 0.6773
- Rewards/margins: 0.6581
- Logps/rejected: -2.3727
- Logps/chosen: -1.7146
- Logits/rejected: 0.3000
- Logits/chosen: 0.1875

## 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: 1e-06
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Sft Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.8248        | 0.2141 | 400  | 0.8255          | 1.3905   | -1.3850        | -1.5360          | 0.5645             | 0.1510          | -1.5360        | -1.3850      | 0.3069          | 0.2210        |
| 0.7884        | 0.4282 | 800  | 0.7811          | 1.4857   | -1.5199        | -1.8625          | 0.6113             | 0.3426          | -1.8625        | -1.5199      | 0.4914          | 0.3895        |
| 0.8073        | 0.6422 | 1200 | 0.7653          | 1.5452   | -1.5531        | -1.9756          | 0.6298             | 0.4226          | -1.9756        | -1.5531      | 0.5229          | 0.4111        |
| 0.7417        | 0.8563 | 1600 | 0.7599          | 1.5652   | -1.5632        | -1.9862          | 0.6484             | 0.4230          | -1.9862        | -1.5632      | 0.5072          | 0.3924        |
| 0.8212        | 1.0704 | 2000 | 0.7518          | 1.5561   | -1.5506        | -2.0302          | 0.6543             | 0.4796          | -2.0302        | -1.5506      | 0.4351          | 0.3208        |
| 0.7326        | 1.2845 | 2400 | 0.7455          | 1.6027   | -1.6077        | -2.1582          | 0.6632             | 0.5505          | -2.1582        | -1.6077      | 0.4993          | 0.3799        |
| 0.7742        | 1.4986 | 2800 | 0.7444          | 1.6196   | -1.6148        | -2.1590          | 0.6632             | 0.5442          | -2.1590        | -1.6148      | 0.4611          | 0.3432        |
| 0.7597        | 1.7127 | 3200 | 0.7438          | 1.6039   | -1.6049        | -2.1441          | 0.6632             | 0.5392          | -2.1441        | -1.6049      | 0.3926          | 0.2796        |
| 0.7128        | 1.9267 | 3600 | 0.7399          | 1.6368   | -1.6446        | -2.2337          | 0.6780             | 0.5891          | -2.2337        | -1.6446      | 0.3607          | 0.2486        |
| 0.6636        | 2.1408 | 4000 | 0.7399          | 1.6738   | -1.6828        | -2.3162          | 0.6780             | 0.6334          | -2.3162        | -1.6828      | 0.3064          | 0.1955        |
| 0.6929        | 2.3549 | 4400 | 0.7421          | 1.7043   | -1.7385        | -2.4029          | 0.6795             | 0.6644          | -2.4029        | -1.7385      | 0.3030          | 0.1902        |
| 0.6939        | 2.5690 | 4800 | 0.7411          | 1.6769   | -1.7078        | -2.3536          | 0.6758             | 0.6458          | -2.3536        | -1.7078      | 0.1986          | 0.0944        |
| 0.6831        | 2.7831 | 5200 | 0.7409          | 1.6830   | -1.7130        | -2.3694          | 0.6766             | 0.6564          | -2.3694        | -1.7130      | 0.3256          | 0.2110        |
| 0.6951        | 2.9972 | 5600 | 0.7405          | 1.6848   | -1.7146        | -2.3727          | 0.6773             | 0.6581          | -2.3727        | -1.7146      | 0.3000          | 0.1875        |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1