---
library_name: transformers
license: other
base_model: trl-lib/qwen1.5-0.5b-sft
tags:
- trl
- simpo
- generated_from_trainer
model-index:
- name: qwen_orpo_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_orpo_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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5590
- Sft Loss: 3.3163
- Rewards/chosen: -3.1855
- Rewards/rejected: -4.1739
- Rewards/accuracies: 0.7226
- Rewards/margins: 0.9884
- Logps/rejected: -4.1739
- Logps/chosen: -3.1855
- Logits/rejected: 0.1645
- Logits/chosen: 0.0521

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7198        | 0.2141 | 400  | 0.7213          | 1.4421   | -1.5116        | -1.6721          | 0.5556             | 0.1605          | -1.6721        | -1.5116      | 0.3831          | 0.2918        |
| 0.6256        | 0.4282 | 800  | 0.6211          | 2.0645   | -2.1064        | -2.5196          | 0.6654             | 0.4133          | -2.5196        | -2.1064      | 0.4328          | 0.3408        |
| 0.6247        | 0.6422 | 1200 | 0.5880          | 2.6367   | -2.5144        | -3.0951          | 0.6966             | 0.5807          | -3.0951        | -2.5144      | 0.4051          | 0.3038        |
| 0.5355        | 0.8563 | 1600 | 0.5751          | 2.5635   | -2.4305        | -2.9974          | 0.7062             | 0.5669          | -2.9974        | -2.4305      | 0.4192          | 0.3133        |
| 0.6075        | 1.0704 | 2000 | 0.5675          | 2.6770   | -2.5347        | -3.1956          | 0.7166             | 0.6609          | -3.1956        | -2.5347      | 0.3536          | 0.2455        |
| 0.5886        | 1.2845 | 2400 | 0.5600          | 2.9406   | -2.8008        | -3.5986          | 0.7292             | 0.7978          | -3.5986        | -2.8008      | 0.2408          | 0.1351        |
| 0.5549        | 1.4986 | 2800 | 0.5573          | 2.8692   | -2.7229        | -3.5062          | 0.7248             | 0.7833          | -3.5062        | -2.7229      | 0.2546          | 0.1468        |
| 0.5785        | 1.7127 | 3200 | 0.5549          | 2.8827   | -2.7303        | -3.5085          | 0.7240             | 0.7782          | -3.5085        | -2.7303      | 0.2599          | 0.1531        |
| 0.5649        | 1.9267 | 3600 | 0.5509          | 2.9742   | -2.8066        | -3.6363          | 0.7240             | 0.8296          | -3.6363        | -2.8066      | 0.2062          | 0.0982        |
| 0.4683        | 2.1408 | 4000 | 0.5601          | 3.3501   | -3.1588        | -4.1100          | 0.7196             | 0.9512          | -4.1100        | -3.1588      | 0.1350          | 0.0257        |
| 0.491         | 2.3549 | 4400 | 0.5604          | 3.3569   | -3.2270        | -4.2111          | 0.7203             | 0.9841          | -4.2111        | -3.2270      | 0.2088          | 0.0922        |
| 0.4967        | 2.5690 | 4800 | 0.5589          | 3.2861   | -3.1626        | -4.1414          | 0.7226             | 0.9787          | -4.1414        | -3.1626      | 0.1660          | 0.0539        |
| 0.439         | 2.7831 | 5200 | 0.5584          | 3.3040   | -3.1772        | -4.1641          | 0.7211             | 0.9869          | -4.1641        | -3.1772      | 0.1462          | 0.0352        |
| 0.4704        | 2.9972 | 5600 | 0.5590          | 3.3163   | -3.1855        | -4.1739          | 0.7226             | 0.9884          | -4.1739        | -3.1855      | 0.1645          | 0.0521        |


### Framework versions

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