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---
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_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_cpo_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: 0.5583
- Sft Loss: 3.4705
- Rewards/chosen: -3.3285
- Rewards/rejected: -4.3810
- Rewards/accuracies: 0.7226
- Rewards/margins: 1.0525
- Logps/rejected: -4.3810
- Logps/chosen: -3.3285
- Logits/rejected: 0.2811
- Logits/chosen: 0.1563

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7019        | 0.2141 | 400  | 0.6977          | 1.4219   | -1.4375        | -1.6032          | 0.5631             | 0.1657          | -1.6032        | -1.4375      | 0.2993          | 0.2138        |
| 0.6225        | 0.4282 | 800  | 0.6192          | 2.0573   | -2.0770        | -2.5396          | 0.6669             | 0.4626          | -2.5396        | -2.0770      | 0.3429          | 0.2570        |
| 0.6242        | 0.6422 | 1200 | 0.5882          | 2.6279   | -2.4850        | -3.1039          | 0.6973             | 0.6190          | -3.1039        | -2.4850      | 0.5237          | 0.4102        |
| 0.5405        | 0.8563 | 1600 | 0.5781          | 2.5442   | -2.4160        | -3.0202          | 0.7092             | 0.6042          | -3.0202        | -2.4160      | 0.4122          | 0.3042        |
| 0.6195        | 1.0704 | 2000 | 0.5673          | 2.7121   | -2.5451        | -3.2527          | 0.7129             | 0.7076          | -3.2527        | -2.5451      | 0.4573          | 0.3371        |
| 0.5895        | 1.2845 | 2400 | 0.5590          | 3.0631   | -2.8962        | -3.7486          | 0.7322             | 0.8524          | -3.7486        | -2.8962      | 0.3362          | 0.2174        |
| 0.5512        | 1.4986 | 2800 | 0.5563          | 2.9053   | -2.7513        | -3.5751          | 0.7203             | 0.8238          | -3.5751        | -2.7513      | 0.2892          | 0.1750        |
| 0.5766        | 1.7127 | 3200 | 0.5520          | 2.9643   | -2.8134        | -3.6655          | 0.7263             | 0.8522          | -3.6655        | -2.8134      | 0.2677          | 0.1562        |
| 0.5625        | 1.9267 | 3600 | 0.5478          | 3.0563   | -2.8597        | -3.7385          | 0.7255             | 0.8788          | -3.7385        | -2.8597      | 0.3670          | 0.2441        |
| 0.4702        | 2.1408 | 4000 | 0.5592          | 3.5119   | -3.3071        | -4.3285          | 0.7240             | 1.0214          | -4.3285        | -3.3071      | 0.2395          | 0.1198        |
| 0.4882        | 2.3549 | 4400 | 0.5601          | 3.5201   | -3.3795        | -4.4355          | 0.7270             | 1.0560          | -4.4355        | -3.3795      | 0.2852          | 0.1603        |
| 0.4952        | 2.5690 | 4800 | 0.5580          | 3.4402   | -3.3065        | -4.3570          | 0.7233             | 1.0505          | -4.3570        | -3.3065      | 0.3210          | 0.1936        |
| 0.4272        | 2.7831 | 5200 | 0.5579          | 3.4523   | -3.3138        | -4.3619          | 0.7233             | 1.0481          | -4.3619        | -3.3138      | 0.3592          | 0.2281        |
| 0.459         | 2.9972 | 5600 | 0.5583          | 3.4705   | -3.3285        | -4.3810          | 0.7226             | 1.0525          | -4.3810        | -3.3285      | 0.2811          | 0.1563        |


### Framework versions

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