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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_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
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