---
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_orpo_entropy
  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

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: 0.5257
- Rewards/chosen: -5.2305
- Rewards/rejected: -6.3460
- Rewards/accuracies: 0.7285
- Rewards/margins: 1.1155
- Logps/rejected: -6.3460
- Logps/chosen: -5.2305
- Logits/rejected: 0.3311
- Logits/chosen: 0.2347

## 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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.7057        | 0.2141 | 400  | 0.7062          | -1.5154        | -1.6776          | 0.5571             | 0.1622          | -1.6776        | -1.5154      | 0.3357          | 0.2498        |
| 0.597         | 0.4282 | 800  | 0.5956          | -2.3371        | -2.7822          | 0.6669             | 0.4451          | -2.7822        | -2.3371      | 0.4528          | 0.3584        |
| 0.5883        | 0.6422 | 1200 | 0.5486          | -3.5511        | -4.2123          | 0.7211             | 0.6612          | -4.2123        | -3.5511      | 0.3923          | 0.2876        |
| 0.4794        | 0.8563 | 1600 | 0.5320          | -3.5255        | -4.2178          | 0.7277             | 0.6924          | -4.2178        | -3.5255      | 0.3881          | 0.2849        |
| 0.5765        | 1.0704 | 2000 | 0.5305          | -3.6701        | -4.4352          | 0.7240             | 0.7651          | -4.4352        | -3.6701      | 0.3104          | 0.1978        |
| 0.5449        | 1.2845 | 2400 | 0.5198          | -4.3149        | -5.2348          | 0.7352             | 0.9199          | -5.2348        | -4.3149      | 0.2247          | 0.1184        |
| 0.518         | 1.4986 | 2800 | 0.5189          | -4.2439        | -5.1423          | 0.7352             | 0.8983          | -5.1423        | -4.2439      | 0.3318          | 0.2186        |
| 0.5602        | 1.7127 | 3200 | 0.5174          | -4.3315        | -5.2509          | 0.7381             | 0.9194          | -5.2509        | -4.3315      | 0.3472          | 0.2362        |
| 0.5482        | 1.9267 | 3600 | 0.5152          | -4.3680        | -5.3320          | 0.7329             | 0.9640          | -5.3320        | -4.3680      | 0.3330          | 0.2233        |
| 0.4259        | 2.1408 | 4000 | 0.5296          | -5.1372        | -6.2156          | 0.7270             | 1.0783          | -6.2156        | -5.1372      | 0.3103          | 0.2143        |
| 0.4141        | 2.3549 | 4400 | 0.5245          | -5.3001        | -6.3996          | 0.7277             | 1.0995          | -6.3996        | -5.3001      | 0.3776          | 0.2775        |
| 0.4481        | 2.5690 | 4800 | 0.5253          | -5.2343        | -6.3529          | 0.7307             | 1.1185          | -6.3529        | -5.2343      | 0.4139          | 0.3107        |
| 0.3925        | 2.7831 | 5200 | 0.5251          | -5.2099        | -6.3202          | 0.7285             | 1.1103          | -6.3202        | -5.2099      | 0.3386          | 0.2411        |
| 0.4044        | 2.9972 | 5600 | 0.5257          | -5.2305        | -6.3460          | 0.7285             | 1.1155          | -6.3460        | -5.2305      | 0.3311          | 0.2347        |


### Framework versions

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