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---
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_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_cUNL_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: 0.5806
- Sft Loss: 4.6392
- Rewards/chosen: -4.6682
- Rewards/rejected: -5.7215
- Rewards/accuracies: 0.7292
- Rewards/margins: 1.0533
- Logps/rejected: -5.7215
- Logps/chosen: -4.6682
- Logits/rejected: 0.0927
- Logits/chosen: 0.0157
## 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.839 | 0.2141 | 400 | 0.8444 | 1.5362 | -1.7061 | -1.9017 | 0.5564 | 0.1956 | -1.9017 | -1.7061 | 0.3788 | 0.2887 |
| 0.6224 | 0.4282 | 800 | 0.6288 | 3.4512 | -3.4767 | -4.0245 | 0.6869 | 0.5479 | -4.0245 | -3.4767 | 0.3857 | 0.3092 |
| 0.6292 | 0.6422 | 1200 | 0.5943 | 3.9913 | -3.8913 | -4.5950 | 0.7211 | 0.7038 | -4.5950 | -3.8913 | 0.3272 | 0.2462 |
| 0.5282 | 0.8563 | 1600 | 0.5852 | 3.8604 | -3.7994 | -4.4882 | 0.7174 | 0.6888 | -4.4882 | -3.7994 | 0.2184 | 0.1456 |
| 0.6187 | 1.0704 | 2000 | 0.5858 | 4.1311 | -4.1032 | -4.8789 | 0.7151 | 0.7757 | -4.8789 | -4.1032 | 0.1497 | 0.0695 |
| 0.5774 | 1.2845 | 2400 | 0.5777 | 4.3179 | -4.2615 | -5.1611 | 0.7277 | 0.8996 | -5.1611 | -4.2615 | 0.2452 | 0.1579 |
| 0.5393 | 1.4986 | 2800 | 0.5736 | 4.3506 | -4.3258 | -5.2226 | 0.7255 | 0.8968 | -5.2226 | -4.3258 | 0.3460 | 0.2569 |
| 0.5981 | 1.7127 | 3200 | 0.5695 | 4.2779 | -4.2570 | -5.1734 | 0.7270 | 0.9164 | -5.1734 | -4.2570 | 0.1928 | 0.1184 |
| 0.5856 | 1.9267 | 3600 | 0.5678 | 4.1129 | -4.0894 | -4.9749 | 0.7337 | 0.8856 | -4.9749 | -4.0894 | 0.1633 | 0.0889 |
| 0.4692 | 2.1408 | 4000 | 0.5829 | 4.6998 | -4.7020 | -5.7415 | 0.7300 | 1.0395 | -5.7415 | -4.7020 | 0.1569 | 0.0750 |
| 0.4844 | 2.3549 | 4400 | 0.5827 | 4.6692 | -4.7235 | -5.7762 | 0.7315 | 1.0527 | -5.7762 | -4.7235 | 0.1451 | 0.0641 |
| 0.488 | 2.5690 | 4800 | 0.5792 | 4.5805 | -4.6213 | -5.6703 | 0.7315 | 1.0490 | -5.6703 | -4.6213 | 0.1281 | 0.0486 |
| 0.4404 | 2.7831 | 5200 | 0.5804 | 4.6279 | -4.6623 | -5.7139 | 0.7300 | 1.0516 | -5.7139 | -4.6623 | 0.0807 | 0.0044 |
| 0.4531 | 2.9972 | 5600 | 0.5806 | 4.6392 | -4.6683 | -5.7215 | 0.7292 | 1.0533 | -5.7215 | -4.6683 | 0.0927 | 0.0156 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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