---
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_ce_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_ce_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: 1.2625
- Rewards/chosen: -1.2622
- Rewards/rejected: -1.3864
- Rewards/accuracies: 0.5475
- Rewards/margins: 0.1242
- Logps/rejected: -1.3864
- Logps/chosen: -1.2622
- Logits/rejected: 0.1431
- Logits/chosen: 0.0760

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 1.2903        | 0.2141 | 400  | 1.3234          | -1.3231        | -1.4418          | 0.5556             | 0.1187          | -1.4418        | -1.3231      | 0.3478          | 0.2657        |
| 1.2586        | 0.4282 | 800  | 1.2926          | -1.2924        | -1.4167          | 0.5482             | 0.1243          | -1.4167        | -1.2924      | 0.3140          | 0.2391        |
| 1.217         | 0.6422 | 1200 | 1.2836          | -1.2833        | -1.4047          | 0.5475             | 0.1213          | -1.4047        | -1.2833      | 0.2906          | 0.2178        |
| 1.299         | 0.8563 | 1600 | 1.2774          | -1.2772        | -1.3985          | 0.5467             | 0.1213          | -1.3985        | -1.2772      | 0.2371          | 0.1683        |
| 1.2617        | 1.0704 | 2000 | 1.2726          | -1.2724        | -1.3958          | 0.5482             | 0.1234          | -1.3958        | -1.2724      | 0.1842          | 0.1180        |
| 1.1894        | 1.2845 | 2400 | 1.2689          | -1.2687        | -1.3924          | 0.5460             | 0.1238          | -1.3924        | -1.2687      | 0.1212          | 0.0586        |
| 1.2779        | 1.4986 | 2800 | 1.2662          | -1.2659        | -1.3880          | 0.5453             | 0.1221          | -1.3880        | -1.2659      | 0.1199          | 0.0573        |
| 1.225         | 1.7127 | 3200 | 1.2650          | -1.2647        | -1.3872          | 0.5490             | 0.1225          | -1.3872        | -1.2647      | 0.1854          | 0.1171        |
| 1.1621        | 1.9267 | 3600 | 1.2636          | -1.2634        | -1.3853          | 0.5475             | 0.1219          | -1.3853        | -1.2634      | 0.1551          | 0.0880        |
| 1.1565        | 2.1408 | 4000 | 1.2633          | -1.2631        | -1.3880          | 0.5482             | 0.1250          | -1.3880        | -1.2631      | 0.0952          | 0.0325        |
| 1.1515        | 2.3549 | 4400 | 1.2629          | -1.2626        | -1.3868          | 0.5467             | 0.1242          | -1.3868        | -1.2626      | 0.0880          | 0.0251        |
| 1.1364        | 2.5690 | 4800 | 1.2625          | -1.2623        | -1.3865          | 0.5467             | 0.1242          | -1.3865        | -1.2623      | 0.1292          | 0.0630        |
| 1.1256        | 2.7831 | 5200 | 1.2626          | -1.2623        | -1.3864          | 0.5475             | 0.1241          | -1.3864        | -1.2623      | 0.1208          | 0.0553        |
| 1.1655        | 2.9972 | 5600 | 1.2625          | -1.2622        | -1.3864          | 0.5475             | 0.1242          | -1.3864        | -1.2622      | 0.1431          | 0.0760        |


### Framework versions

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