---
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_qfUNL_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_qfUNL_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: 0.6510
- Rewards/chosen: -1.7989
- Rewards/rejected: -2.5830
- Rewards/accuracies: 0.6736
- Rewards/margins: 0.7841
- Logps/rejected: -2.5830
- Logps/chosen: -1.7989
- Logits/rejected: 0.0192
- Logits/chosen: -0.0604

## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6781        | 0.2141 | 400  | 0.6873          | -1.6444        | -1.8233          | 0.5475             | 0.1789          | -1.8233        | -1.6444      | 0.2857          | 0.1996        |
| 0.6757        | 0.4282 | 800  | 0.6641          | -1.6348        | -1.9815          | 0.6239             | 0.3467          | -1.9815        | -1.6348      | 0.3665          | 0.2730        |
| 0.6569        | 0.6422 | 1200 | 0.6602          | -1.7060        | -2.1644          | 0.6424             | 0.4584          | -2.1644        | -1.7060      | 0.2601          | 0.1749        |
| 0.6562        | 0.8563 | 1600 | 0.6584          | -1.8368        | -2.3836          | 0.6513             | 0.5468          | -2.3836        | -1.8368      | 0.1796          | 0.0944        |
| 0.6883        | 1.0704 | 2000 | 0.6545          | -1.7098        | -2.2986          | 0.6639             | 0.5888          | -2.2986        | -1.7098      | 0.2146          | 0.1248        |
| 0.6581        | 1.2845 | 2400 | 0.6533          | -1.7444        | -2.3861          | 0.6691             | 0.6417          | -2.3861        | -1.7444      | 0.1530          | 0.0644        |
| 0.6444        | 1.4986 | 2800 | 0.6537          | -1.7815        | -2.4833          | 0.6684             | 0.7018          | -2.4833        | -1.7815      | 0.0665          | -0.0145       |
| 0.6575        | 1.7127 | 3200 | 0.6520          | -1.7922        | -2.5114          | 0.6654             | 0.7192          | -2.5114        | -1.7922      | 0.1107          | 0.0260        |
| 0.6481        | 1.9267 | 3600 | 0.6507          | -1.7358        | -2.4632          | 0.6736             | 0.7275          | -2.4632        | -1.7358      | 0.0939          | 0.0113        |
| 0.607         | 2.1408 | 4000 | 0.6506          | -1.7686        | -2.5161          | 0.6751             | 0.7475          | -2.5161        | -1.7686      | 0.0842          | 0.0005        |
| 0.6294        | 2.3549 | 4400 | 0.6514          | -1.8215        | -2.5986          | 0.6714             | 0.7771          | -2.5986        | -1.8215      | 0.0008          | -0.0778       |
| 0.6098        | 2.5690 | 4800 | 0.6507          | -1.7918        | -2.5693          | 0.6766             | 0.7775          | -2.5693        | -1.7918      | 0.0735          | -0.0103       |
| 0.6302        | 2.7831 | 5200 | 0.6507          | -1.7943        | -2.5780          | 0.6751             | 0.7837          | -2.5780        | -1.7943      | 0.0395          | -0.0418       |
| 0.6181        | 2.9972 | 5600 | 0.6510          | -1.7989        | -2.5830          | 0.6736             | 0.7841          | -2.5830        | -1.7989      | 0.0192          | -0.0604       |


### Framework versions

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