---
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_cUNL_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_cUNL_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: 0.5196
- Rewards/chosen: -7.4572
- Rewards/rejected: -8.6117
- Rewards/accuracies: 0.7285
- Rewards/margins: 1.1545
- Logps/rejected: -8.6117
- Logps/chosen: -7.4572
- Logits/rejected: 0.5435
- Logits/chosen: 0.4914

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.8222        | 0.2141 | 400  | 0.8285          | -1.7118        | -1.9086          | 0.5534             | 0.1968          | -1.9086        | -1.7118      | 0.3777          | 0.2894        |
| 0.5698        | 0.4282 | 800  | 0.5834          | -4.3085        | -4.8785          | 0.6899             | 0.5700          | -4.8785        | -4.3085      | 0.4424          | 0.3680        |
| 0.5645        | 0.6422 | 1200 | 0.5407          | -5.3672        | -6.1336          | 0.7196             | 0.7664          | -6.1336        | -5.3672      | 0.5839          | 0.4867        |
| 0.4723        | 0.8563 | 1600 | 0.5308          | -6.0239        | -6.7829          | 0.7188             | 0.7590          | -6.7829        | -6.0239      | 0.4449          | 0.3580        |
| 0.5671        | 1.0704 | 2000 | 0.5245          | -6.1299        | -6.9744          | 0.7270             | 0.8445          | -6.9744        | -6.1299      | 0.5458          | 0.4536        |
| 0.5184        | 1.2845 | 2400 | 0.5194          | -6.2767        | -7.2502          | 0.7300             | 0.9736          | -7.2502        | -6.2767      | 0.5423          | 0.4595        |
| 0.4823        | 1.4986 | 2800 | 0.5166          | -6.4303        | -7.3916          | 0.7285             | 0.9613          | -7.3916        | -6.4303      | 0.4681          | 0.4003        |
| 0.5627        | 1.7127 | 3200 | 0.5134          | -6.6572        | -7.6688          | 0.7352             | 1.0116          | -7.6688        | -6.6572      | 0.5174          | 0.4489        |
| 0.5355        | 1.9267 | 3600 | 0.5093          | -6.3599        | -7.3630          | 0.7352             | 1.0031          | -7.3630        | -6.3599      | 0.4672          | 0.4010        |
| 0.3968        | 2.1408 | 4000 | 0.5234          | -7.4930        | -8.6276          | 0.7248             | 1.1346          | -8.6276        | -7.4930      | 0.5678          | 0.5128        |
| 0.4135        | 2.3549 | 4400 | 0.5203          | -7.4952        | -8.6565          | 0.7240             | 1.1613          | -8.6565        | -7.4952      | 0.4661          | 0.4203        |
| 0.4277        | 2.5690 | 4800 | 0.5189          | -7.3524        | -8.5007          | 0.7270             | 1.1483          | -8.5007        | -7.3524      | 0.5701          | 0.5143        |
| 0.3999        | 2.7831 | 5200 | 0.5187          | -7.4281        | -8.5789          | 0.7292             | 1.1507          | -8.5789        | -7.4281      | 0.5522          | 0.4986        |
| 0.3855        | 2.9972 | 5600 | 0.5195          | -7.4572        | -8.6117          | 0.7285             | 1.1545          | -8.6117        | -7.4572      | 0.5435          | 0.4914        |


### Framework versions

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