---
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_fUNL_entropy_0_01
  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_fUNL_entropy_0_01

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: 0.0504
- Sft Loss: 4.0281
- Rewards/chosen: -4.4231
- Rewards/rejected: -5.1418
- Rewards/accuracies: 0.6862
- Rewards/margins: 0.7187
- Logps/rejected: -5.1418
- Logps/chosen: -4.4231
- Logits/rejected: -0.2955
- Logits/chosen: -0.3687

## 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 | Sft Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.0548        | 0.2141 | 400  | 0.0557          | 4.8295   | -5.3467        | -5.4723          | 0.5326             | 0.1256          | -5.4723        | -5.3467      | 0.1095          | -0.0277       |
| 0.0537        | 0.4282 | 800  | 0.0529          | 4.1330   | -4.6614        | -4.9903          | 0.6024             | 0.3289          | -4.9903        | -4.6614      | 0.2188          | 0.0763        |
| 0.0545        | 0.6422 | 1200 | 0.0523          | 4.2856   | -4.6580        | -5.0486          | 0.6350             | 0.3906          | -5.0486        | -4.6580      | 0.0914          | -0.0257       |
| 0.0518        | 0.8563 | 1600 | 0.0519          | 4.0636   | -4.5007        | -4.9176          | 0.6313             | 0.4169          | -4.9176        | -4.5007      | 0.0782          | -0.0290       |
| 0.0537        | 1.0704 | 2000 | 0.0517          | 3.9662   | -4.4270        | -4.8924          | 0.6469             | 0.4654          | -4.8924        | -4.4270      | -0.1550         | -0.2400       |
| 0.0533        | 1.2845 | 2400 | 0.0514          | 4.4069   | -4.8229        | -5.4257          | 0.6632             | 0.6028          | -5.4257        | -4.8229      | -0.1556         | -0.2460       |
| 0.0522        | 1.4986 | 2800 | 0.0511          | 4.2244   | -4.5446        | -5.1374          | 0.6803             | 0.5928          | -5.1374        | -4.5446      | -0.2984         | -0.3849       |
| 0.053         | 1.7127 | 3200 | 0.0508          | 4.1193   | -4.4960        | -5.1073          | 0.6691             | 0.6113          | -5.1073        | -4.4960      | -0.2032         | -0.2947       |
| 0.0538        | 1.9267 | 3600 | 0.0505          | 4.0434   | -4.4193        | -5.0638          | 0.6847             | 0.6445          | -5.0638        | -4.4193      | -0.2476         | -0.3292       |
| 0.0504        | 2.1408 | 4000 | 0.0505          | 4.0585   | -4.4646        | -5.1658          | 0.6840             | 0.7011          | -5.1658        | -4.4646      | -0.2103         | -0.2919       |
| 0.053         | 2.3549 | 4400 | 0.0505          | 4.0905   | -4.4767        | -5.1722          | 0.6840             | 0.6956          | -5.1722        | -4.4767      | -0.2850         | -0.3632       |
| 0.0525        | 2.5690 | 4800 | 0.0504          | 4.0700   | -4.4483        | -5.1426          | 0.6832             | 0.6943          | -5.1426        | -4.4483      | -0.1890         | -0.2741       |
| 0.0509        | 2.7831 | 5200 | 0.0504          | 4.0135   | -4.3932        | -5.0993          | 0.6855             | 0.7061          | -5.0993        | -4.3932      | -0.1516         | -0.2376       |
| 0.0504        | 2.9972 | 5600 | 0.0504          | 4.0281   | -4.4231        | -5.1418          | 0.6862             | 0.7187          | -5.1418        | -4.4231      | -0.2955         | -0.3687       |


### Framework versions

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