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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_orpo_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_orpo_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: 0.5245
- Rewards/chosen: -9.9757
- Rewards/rejected: -11.1054
- Rewards/accuracies: 0.7240
- Rewards/margins: 1.1296
- Logps/rejected: -11.1054
- Logps/chosen: -9.9757
- Logits/rejected: 0.9577
- Logits/chosen: 0.9163
- Semantic Entropy: 0.0013
## 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 | Semantic Entropy |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:----------------:|
| 1.0119 | 0.2141 | 400 | 1.0132 | -1.7930 | -2.0280 | 0.5660 | 0.2350 | -2.0280 | -1.7930 | 0.3600 | 0.2738 | 0.6132 |
| 0.5924 | 0.4282 | 800 | 0.5851 | -6.7409 | -7.2987 | 0.6810 | 0.5578 | -7.2987 | -6.7409 | 0.5386 | 0.4884 | 0.0131 |
| 0.5951 | 0.6422 | 1200 | 0.5522 | -7.9883 | -8.6813 | 0.7062 | 0.6931 | -8.6813 | -7.9883 | 0.7969 | 0.7507 | 0.0050 |
| 0.4796 | 0.8563 | 1600 | 0.5406 | -8.4790 | -9.1974 | 0.7047 | 0.7184 | -9.1974 | -8.4790 | 0.9158 | 0.8517 | 0.0035 |
| 0.5834 | 1.0704 | 2000 | 0.5344 | -8.7256 | -9.5131 | 0.7159 | 0.7875 | -9.5131 | -8.7256 | 0.8620 | 0.7784 | 0.0027 |
| 0.5261 | 1.2845 | 2400 | 0.5313 | -8.7103 | -9.6511 | 0.7136 | 0.9408 | -9.6511 | -8.7103 | 0.8723 | 0.8012 | 0.0029 |
| 0.4879 | 1.4986 | 2800 | 0.5264 | -8.6267 | -9.5330 | 0.7218 | 0.9063 | -9.5330 | -8.6267 | 0.7496 | 0.6896 | 0.0033 |
| 0.5524 | 1.7127 | 3200 | 0.5207 | -8.8757 | -9.8346 | 0.7166 | 0.9589 | -9.8346 | -8.8757 | 0.9052 | 0.8485 | 0.0030 |
| 0.5311 | 1.9267 | 3600 | 0.5170 | -9.0983 | -10.0747 | 0.7233 | 0.9765 | -10.0747 | -9.0983 | 0.8342 | 0.7884 | 0.0024 |
| 0.3953 | 2.1408 | 4000 | 0.5261 | -9.8407 | -10.9409 | 0.7196 | 1.1002 | -10.9409 | -9.8407 | 0.9782 | 0.9286 | 0.0015 |
| 0.428 | 2.3549 | 4400 | 0.5250 | -9.9515 | -11.0890 | 0.7211 | 1.1375 | -11.0890 | -9.9515 | 0.9721 | 0.9215 | 0.0013 |
| 0.4394 | 2.5690 | 4800 | 0.5238 | -9.8173 | -10.9421 | 0.7255 | 1.1248 | -10.9421 | -9.8173 | 0.8956 | 0.8550 | 0.0014 |
| 0.4221 | 2.7831 | 5200 | 0.5239 | -9.9581 | -11.0861 | 0.7248 | 1.1280 | -11.0861 | -9.9581 | 0.9048 | 0.8672 | 0.0013 |
| 0.4023 | 2.9972 | 5600 | 0.5245 | -9.9757 | -11.1054 | 0.7240 | 1.1296 | -11.1054 | -9.9757 | 0.9577 | 0.9163 | 0.0013 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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