---
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_unl_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_unl_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: 1.6475
- Rewards/chosen: -1.3030
- Rewards/rejected: -1.4992
- Rewards/accuracies: 0.5712
- Rewards/margins: 0.1962
- Logps/rejected: -1.4992
- Logps/chosen: -1.3030
- Logits/rejected: 0.0833
- Logits/chosen: 0.0165

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 1.6549        | 0.2141 | 400  | 1.6939          | -1.3375        | -1.4631          | 0.5564             | 0.1256          | -1.4631        | -1.3375      | 0.3664          | 0.2799        |
| 1.6692        | 0.4282 | 800  | 1.6718          | -1.3151        | -1.4532          | 0.5579             | 0.1381          | -1.4532        | -1.3151      | 0.3708          | 0.2889        |
| 1.6206        | 0.6422 | 1200 | 1.6640          | -1.3083        | -1.4522          | 0.5564             | 0.1438          | -1.4522        | -1.3083      | 0.3523          | 0.2714        |
| 1.6566        | 0.8563 | 1600 | 1.6600          | -1.3096        | -1.4585          | 0.5593             | 0.1488          | -1.4585        | -1.3096      | 0.3578          | 0.2764        |
| 1.7104        | 1.0704 | 2000 | 1.6553          | -1.3006        | -1.4569          | 0.5660             | 0.1563          | -1.4569        | -1.3006      | 0.2528          | 0.1781        |
| 1.6123        | 1.2845 | 2400 | 1.6521          | -1.3029        | -1.4743          | 0.5668             | 0.1713          | -1.4743        | -1.3029      | 0.1650          | 0.0956        |
| 1.6688        | 1.4986 | 2800 | 1.6486          | -1.3000        | -1.4729          | 0.5690             | 0.1729          | -1.4729        | -1.3000      | 0.1751          | 0.1050        |
| 1.6012        | 1.7127 | 3200 | 1.6495          | -1.3009        | -1.4722          | 0.5668             | 0.1713          | -1.4722        | -1.3009      | 0.2139          | 0.1401        |
| 1.5646        | 1.9267 | 3600 | 1.6478          | -1.2987        | -1.4778          | 0.5705             | 0.1791          | -1.4778        | -1.2987      | 0.1771          | 0.1052        |
| 1.5351        | 2.1408 | 4000 | 1.6470          | -1.3020        | -1.4952          | 0.5712             | 0.1932          | -1.4952        | -1.3020      | 0.1238          | 0.0547        |
| 1.5307        | 2.3549 | 4400 | 1.6469          | -1.3054        | -1.5043          | 0.5712             | 0.1988          | -1.5043        | -1.3054      | 0.0587          | -0.0064       |
| 1.5433        | 2.5690 | 4800 | 1.6472          | -1.3037        | -1.5017          | 0.5727             | 0.1980          | -1.5017        | -1.3037      | 0.1609          | 0.0880        |
| 1.5671        | 2.7831 | 5200 | 1.6473          | -1.3030        | -1.4994          | 0.5720             | 0.1964          | -1.4994        | -1.3030      | 0.0927          | 0.0252        |
| 1.5482        | 2.9972 | 5600 | 1.6475          | -1.3030        | -1.4992          | 0.5712             | 0.1962          | -1.4992        | -1.3030      | 0.0833          | 0.0165        |


### Framework versions

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