---
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_uncCPO_entropy_0_01
  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_uncCPO_entropy_0_01

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: 0.0500
- Sft Loss: 3.9220
- Rewards/chosen: -4.3252
- Rewards/rejected: -5.1044
- Rewards/accuracies: 0.6892
- Rewards/margins: 0.7793
- Logps/rejected: -5.1044
- Logps/chosen: -4.3252
- Logits/rejected: 0.1444
- Logits/chosen: 0.0509

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0563        | 0.2141 | 400  | 0.0573          | 4.8352   | -5.7454        | -6.0246          | 0.5445             | 0.2792          | -6.0246        | -5.7454      | 0.6512          | 0.5372        |
| 0.0533        | 0.4282 | 800  | 0.0524          | 4.2340   | -4.6954        | -5.0777          | 0.6157             | 0.3823          | -5.0777        | -4.6954      | 0.2939          | 0.1644        |
| 0.0533        | 0.6422 | 1200 | 0.0518          | 4.1504   | -4.5198        | -5.0186          | 0.6484             | 0.4989          | -5.0186        | -4.5198      | 0.4014          | 0.2684        |
| 0.0508        | 0.8563 | 1600 | 0.0512          | 4.0690   | -4.5220        | -5.0081          | 0.6491             | 0.4862          | -5.0081        | -4.5220      | 0.2498          | 0.1344        |
| 0.0529        | 1.0704 | 2000 | 0.0508          | 3.9195   | -4.3917        | -4.9646          | 0.6521             | 0.5729          | -4.9646        | -4.3917      | 0.3268          | 0.2181        |
| 0.0522        | 1.2845 | 2400 | 0.0504          | 4.1797   | -4.6133        | -5.2771          | 0.6647             | 0.6638          | -5.2771        | -4.6133      | 0.2727          | 0.1622        |
| 0.0515        | 1.4986 | 2800 | 0.0504          | 4.0933   | -4.4442        | -5.0786          | 0.6825             | 0.6344          | -5.0786        | -4.4442      | 0.2050          | 0.0984        |
| 0.0526        | 1.7127 | 3200 | 0.0503          | 4.0886   | -4.4943        | -5.1537          | 0.6751             | 0.6594          | -5.1537        | -4.4943      | 0.2002          | 0.0920        |
| 0.0533        | 1.9267 | 3600 | 0.0501          | 3.9857   | -4.3809        | -5.1003          | 0.6825             | 0.7195          | -5.1003        | -4.3809      | 0.1348          | 0.0421        |
| 0.0493        | 2.1408 | 4000 | 0.0500          | 3.9751   | -4.3954        | -5.1537          | 0.6840             | 0.7583          | -5.1537        | -4.3954      | 0.3029          | 0.1980        |
| 0.0522        | 2.3549 | 4400 | 0.0500          | 3.9820   | -4.4013        | -5.1632          | 0.6869             | 0.7619          | -5.1632        | -4.4013      | 0.2139          | 0.1131        |
| 0.0513        | 2.5690 | 4800 | 0.0500          | 3.9732   | -4.3709        | -5.1160          | 0.6944             | 0.7451          | -5.1160        | -4.3709      | 0.1787          | 0.0785        |
| 0.0498        | 2.7831 | 5200 | 0.0500          | 3.9372   | -4.3318        | -5.0969          | 0.6892             | 0.7651          | -5.0969        | -4.3318      | 0.2138          | 0.1134        |
| 0.0496        | 2.9972 | 5600 | 0.0500          | 3.9220   | -4.3252        | -5.1044          | 0.6892             | 0.7793          | -5.1044        | -4.3252      | 0.1444          | 0.0509        |


### Framework versions

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